数据清洗算法

algorithm/algorithm-boot/pom.xml

@@ -99,6 +99,11 @@
             <artifactId>liteflow-rule-nacos</artifactId>
             <version>2.11.2</version>
         </dependency>
+        <dependency>
+            <groupId>com.njcn</groupId>
+            <artifactId>pq-device-api</artifactId>
+            <version>${project.version}</version>
+        </dependency>
     </dependencies>
 
     <build>

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/executor/MeasurementExecutor.java

@@ -29,7 +29,8 @@ public class MeasurementExecutor extends BaseExecutor {
     private IDataCleanService dataCleanService;
 
     /**
-     * 数据清洗（dataV）
+     * 数据清洗 电压表
+     * dataV表
      * @author xy
      */
     @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataVClean", nodeType = NodeTypeEnum.COMMON)
@@ -41,6 +42,120 @@ public class MeasurementExecutor extends BaseExecutor {
         dataCleanService.dataVCleanHandler(bindCmp.getRequestData());
     }
 
+    /**
+     * 数据清洗 电流表
+     * dataI表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataIClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataICleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataIClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataICleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataICleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗 长闪表
+     * dataPlt表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataPltClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataPltCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataPltClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataPltCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataPltCleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗 间谐波电压表
+     * DataInHarmV表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataInHarmVClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataInHarmVCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataInHarmVClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataInHarmVCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataInHarmVCleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗 谐波电压含有率
+     * DataHarmRateV表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataHarmRateVClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataHarmRateVCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataHarmRateVClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataHarmRateVCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataHarmRateVCleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗 有功功率表
+     * DataHarmPowerP表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataHarmPowerPClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataHarmPowerPCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataHarmPowerPClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataHarmPowerPCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataHarmPowerPCleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗 谐波电压角度表
+     * DataHarmPhasicV表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataHarmPhasicVClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataHarmPhasicVCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataHarmPhasicVClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataHarmPhasicVCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataHarmPhasicVCleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗  电压波动表
+     * DataFluc表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataFlucClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataFlucCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataFlucClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataFlucCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataFlucCleanHandler(bindCmp.getRequestData());
+    }
+
+    /**
+     * 数据清洗
+     * DataFlicker表
+     * @author xy
+     */
+    @LiteflowMethod(value = LiteFlowMethodEnum.IS_ACCESS, nodeId = "dataFlickerClean", nodeType = NodeTypeEnum.COMMON)
+    public boolean dataFlickerCleanAccess(NodeComponent bindCmp) {
+        return isAccess(bindCmp);
+    }
+    @LiteflowMethod(value = LiteFlowMethodEnum.PROCESS, nodeId = "dataFlickerClean", nodeType = NodeTypeEnum.COMMON)
+    public void dataFlickerCleanProcess(NodeComponent bindCmp) {
+        dataCleanService.dataFlickerCleanHandler(bindCmp.getRequestData());
+    }
+
+
+
     /**
      * 监测点报表_日表(r_stat_data_*_d)
      * @author xy

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/service/line/IDataCleanService.java

@@ -9,9 +9,73 @@ public interface IDataCleanService {
 
     /***
      * dataV数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
      * @author xy
      * @param calculatedParam 查询条件
      */
     void dataVCleanHandler(CalculatedParam calculatedParam);
 
+    /***
+     * dataI数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataICleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataPlt数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataPltCleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataInHarmV数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataInHarmVCleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataHarmRateV数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataHarmRateVCleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataHarmPowerP数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataHarmPowerPCleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataHarmPhasicV数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataHarmPhasicVCleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataFluc数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataFlucCleanHandler(CalculatedParam calculatedParam);
+
+    /***
+     * dataFlicker数据清洗
+     * 不标记原始数据，将异常数据查询出来重新存储至详情表中
+     * @author xy
+     * @param calculatedParam 查询条件
+     */
+    void dataFlickerCleanHandler(CalculatedParam calculatedParam);
 }

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/serviceimpl/line/DataCleanServiceImpl.java

@@ -3,10 +3,16 @@ package com.njcn.algorithm.serviceimpl.line;
 import cn.hutool.core.collection.CollUtil;
 import com.njcn.algorithm.pojo.bo.CalculatedParam;
 import com.njcn.algorithm.service.line.IDataCleanService;
-import com.njcn.dataProcess.api.DataVFeignClient;
+import com.njcn.dataProcess.api.*;
+import com.njcn.dataProcess.enums.DataCleanEnum;
+import com.njcn.dataProcess.param.DataCleanParam;
 import com.njcn.dataProcess.param.LineCountEvaluateParam;
-import com.njcn.dataProcess.pojo.dto.DataVDto;
+import com.njcn.dataProcess.pojo.dto.*;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+import com.njcn.dataProcess.util.DataCommonUtils;
 import com.njcn.dataProcess.util.TimeUtils;
+import com.njcn.device.pq.api.LineFeignClient;
+import com.njcn.device.pq.pojo.vo.LineDetailVO;
 import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.ListUtils;
@@ -15,8 +21,11 @@ import org.slf4j.LoggerFactory;
 import org.springframework.stereotype.Component;
 
 import javax.annotation.Resource;
-import java.util.ArrayList;
-import java.util.List;
+import java.lang.reflect.Method;
+import java.time.LocalDateTime;
+import java.util.*;
+import java.util.function.Function;
+import java.util.stream.Collectors;
 
 /**
  * @author xy
@@ -31,26 +40,833 @@ public class DataCleanServiceImpl implements IDataCleanService {
 
     @Resource
     private DataVFeignClient dataVFeignClient;
+    @Resource
+    private DataIFeignClient dataIFeignClient;
+    @Resource
+    private DataPltFeignClient dataPltFeignClient;
+    @Resource
+    private DataInharmVFeignClient dataInharmVFeignClient;
+    @Resource
+    private DataHarmRateVFeignClient dataHarmRateVFeignClient;
+    @Resource
+    private DataHarmpowerPFeignClient dataHarmpowerPFeignClient;
+    @Resource
+    private DataHarmphasicVFeignClient dataHarmphasicVFeignClient;
+    @Resource
+    private DataFlucFeignClient dataFlucFeignClient;
+    @Resource
+    private DataFlickerFeignClient dataFlickerFeignClient;
+    @Resource
+    private PqDataVerifyFeignClient pqDataVerifyFeignClient;
+    @Resource
+    private PqReasonableRangeFeignClient pqReasonableRangeFeignClient;
+    @Resource
+    private LineFeignClient lineFeignClient;
+
 
     @Override
     public void dataVCleanHandler(CalculatedParam calculatedParam) {
-        List<DataVDto> result = new ArrayList<>();
+        logger.info("{},dataV表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataV.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        List<LineDetailVO.Detail> lineDetail = lineFeignClient.getLineDetailByIds(lineList).getData();
+        if (CollUtil.isEmpty(lineDetail)) {
+            logger.error("监测点集合为空，无法计算!");
+            return;
+        }
+        Map<String,LineDetailVO.Detail> lineMap = lineDetail.stream().collect(Collectors.toMap(LineDetailVO.Detail::getLineId, Function.identity()));
+        //数据分片处理
         LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
         lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
         lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
-        List<List<String>> pendingIds = ListUtils.partition(calculatedParam.getIdList(),NUM);
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
         pendingIds.forEach(list->{
             lineParam.setLineId(list);
             List<DataVDto> partList = dataVFeignClient.getRawData(lineParam).getData();
             if (CollUtil.isNotEmpty(partList)) {
                 partList.forEach(item->{
-                    item.setAbnormalFlag(0);
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataV(map, lineMap.get(item.getLineId()),item);
+                    result.addAll(pqDataVerifies);
                 });
-                result.addAll(partList);
             }
         });
         if (CollUtil.isNotEmpty(result)) {
-            dataVFeignClient.addInfluxDbList(result);
+            pqDataVerifyFeignClient.insertData(result);
         }
     }
+
+    @Override
+    public void dataICleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataI表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataI.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        List<LineDetailVO.Detail> lineDetail = lineFeignClient.getLineDetailByIds(lineList).getData();
+        if (CollUtil.isEmpty(lineDetail)) {
+            logger.error("监测点集合为空，无法计算!");
+            return;
+        }
+        Map<String,LineDetailVO.Detail> lineMap = lineDetail.stream().collect(Collectors.toMap(LineDetailVO.Detail::getLineId, Function.identity()));
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataIDto> partList = dataIFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataI(map, lineMap.get(item.getLineId()),item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataPltCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataPlt表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataPlt.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataPltDto> partList = dataPltFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataPlt(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataInHarmVCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataInHarmV表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataInHarmV.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataHarmDto> partList = dataInharmVFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataInHarmV(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataHarmRateVCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataHarmRateV表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataHarmRateV.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataHarmDto> partList = dataHarmRateVFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataHarmRateV(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataHarmPowerPCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataHarmPowerP表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataHarmPowerP.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataPowerPDto> partList = dataHarmpowerPFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataHarmPowerP(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataHarmPhasicVCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataHarmPhasicV表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataHarmPhasicV.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataHarmDto> partList = dataHarmphasicVFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataHarmPhasicV(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataFlucCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataFluc表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataFluc.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataFlucDto> partList = dataFlucFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataFluc(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+    @Override
+    public void dataFlickerCleanHandler(CalculatedParam calculatedParam) {
+        logger.info("{},dataFlicker表异常数据算法执行=====》", LocalDateTime.now());
+        List<PqDataVerify> result = new ArrayList<>();
+        //获取标准
+        Map<String, PqReasonableRangeDto> map = getStandardData(DataCleanEnum.DataFlicker.getCode());
+        //获取监测点台账信息
+        List<String> lineList = calculatedParam.getIdList();
+        //数据分片处理
+        LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
+        lineParam.setStartTime(TimeUtils.getBeginOfDay(calculatedParam.getDataDate()));
+        lineParam.setEndTime(TimeUtils.getEndOfDay(calculatedParam.getDataDate()));
+        List<List<String>> pendingIds = ListUtils.partition(lineList,NUM);
+        pendingIds.forEach(list->{
+            lineParam.setLineId(list);
+            List<DataFlickerDto> partList = dataFlickerFeignClient.getRawData(lineParam).getData();
+            if (CollUtil.isNotEmpty(partList)) {
+                partList.forEach(item->{
+                    //数据清洗
+                    List<PqDataVerify> pqDataVerifies = judgeDataFlicker(map,item);
+                    result.addAll(pqDataVerifies);
+                });
+            }
+        });
+        if (CollUtil.isNotEmpty(result)) {
+            pqDataVerifyFeignClient.insertData(result);
+        }
+    }
+
+
+    /**
+     * 获取标准数据的范围
+     */
+    public Map<String, PqReasonableRangeDto> getStandardData(String tableName) {
+        Map<String, PqReasonableRangeDto> pqReasonableRangeDtoMap = new HashMap<>();
+        DataCleanParam param = new DataCleanParam();
+        param.setSystemType(DataCleanEnum.Pqs.getCode());
+        param.setDataSource(DataCleanEnum.InfluxDB.getCode());
+        param.setTableName(tableName);
+        List<PqReasonableRangeDto> list = pqReasonableRangeFeignClient.getData(param).getData();
+        if (CollUtil.isNotEmpty(list)) {
+            pqReasonableRangeDtoMap = list.stream().collect(Collectors.toMap(PqReasonableRangeDto::getIndexCode, Function.identity()));
+        }
+        return pqReasonableRangeDtoMap;
+    }
+
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataV(Map<String, PqReasonableRangeDto> map, LineDetailVO.Detail line, DataVDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto;
+        List<String> phaseList;
+        //频率判断
+        pqReasonableRangeDto = map.get(DataCleanEnum.Freq.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getFreq() < pqReasonableRangeDto.getMinValue() || dto.getFreq() > pqReasonableRangeDto.getMaxValue()) {
+                //log.info("dataV-频率数据异常,已清洗!数据值:{},数据时间:{}", dto.getFreq(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getFreq()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+
+        //频率偏差判断
+        pqReasonableRangeDto = map.get(DataCleanEnum.FreqDev.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getFreqDev() < pqReasonableRangeDto.getMinValue() || dto.getFreqDev() > pqReasonableRangeDto.getMaxValue()) {
+                //log.info("dataV-频率偏差数据异常,已清洗!数据值:{},数据时间:{}", dto.getFreqDev(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getFreqDev()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+
+        //相电压有效值
+        pqReasonableRangeDto = map.get(DataCleanEnum.RmsV.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getRms() < (pqReasonableRangeDto.getMinValue()* DataCommonUtils.getVoltageData(line.getVoltageLevel()))
+                    || dto.getRms() > (pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))) {
+                //log.info("dataV-相电压有效值数据异常,已清洗!数据值:{},数据时间:{}", dto.getRms(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getRms()
+                        ,pqReasonableRangeDto.getMinValue()* DataCommonUtils.getVoltageData(line.getVoltageLevel())
+                        ,pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()));
+                list.add(pqDataVerify);
+            }
+        }
+
+        //正序电压
+        pqReasonableRangeDto = map.get(DataCleanEnum.VPos.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVPos() < (pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))
+                    || dto.getVPos() > (pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))) {
+                //log.info("dataV-正序电压数据异常,已清洗!数据值:{},数据时间:{}", dto.getVPos(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVPos()
+                        ,pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel())
+                        ,pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()));
+                list.add(pqDataVerify);
+            }
+        }
+
+        //负序电压
+        pqReasonableRangeDto = map.get(DataCleanEnum.VNeg.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVNeg() < (pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))
+                    || dto.getVNeg() > (pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))) {
+                //log.info("dataV-负序电压数据异常,已清洗!数据值:{},数据时间:{}", dto.getVNeg(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVNeg()
+                        ,pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel())
+                        ,pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()));
+                list.add(pqDataVerify);
+            }
+        }
+
+        //零序电压
+        pqReasonableRangeDto = map.get(DataCleanEnum.VZero.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVZero() < (pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))
+                    || dto.getVZero() > (pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))) {
+                //log.info("dataV-零序电压数据异常,已清洗!数据值:{},数据时间:{}", dto.getVZero(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVZero()
+                        ,pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel())
+                        ,pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()));
+                list.add(pqDataVerify);
+            }
+        }
+
+        //电压不平衡度
+        pqReasonableRangeDto = map.get(DataCleanEnum.VUnbalance.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVUnbalance() < pqReasonableRangeDto.getMinValue() || dto.getVUnbalance() > pqReasonableRangeDto.getMaxValue()) {
+                //log.info("dataV-电压不平衡度数据异常,已清洗!数据值:{},数据时间:{}", dto.getVUnbalance(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVUnbalance()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+
+        //线电压有效值
+        pqReasonableRangeDto = map.get(DataCleanEnum.RmsLvr.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getRmsLvr() < (pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))
+                    || dto.getRmsLvr() > (pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))) {
+                //log.info("dataV-线电压有效值数据异常,已清洗!数据值:{},数据时间:{}", dto.getRmsLvr(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getRmsLvr()
+                        ,pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel())
+                        ,pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()));
+                list.add(pqDataVerify);
+            }
+        }
+
+        //线电压正偏差
+        pqReasonableRangeDto = map.get(DataCleanEnum.VuDev.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVuDev() < pqReasonableRangeDto.getMinValue() || dto.getVuDev() > pqReasonableRangeDto.getMaxValue()) {
+                //log.info("dataV-线电压正偏差数据异常,已清洗!数据值:{},数据时间:{}", dto.getVuDev(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVuDev()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+
+        //线电压负偏差
+        pqReasonableRangeDto = map.get(DataCleanEnum.VlDev.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVlDev() < pqReasonableRangeDto.getMinValue() || dto.getVlDev() > pqReasonableRangeDto.getMaxValue()) {
+                //log.info("dataV-线电压负偏差数据异常,已清洗!数据值:{},数据时间:{}", dto.getVlDev(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVlDev()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+
+        //电压总谐波畸变率
+        pqReasonableRangeDto = map.get(DataCleanEnum.VThd.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getVThd() < pqReasonableRangeDto.getMinValue() || dto.getVThd() > pqReasonableRangeDto.getMaxValue()) {
+                //log.info("dataV-电压总谐波畸变率数据异常,已清洗!数据值:{},数据时间:{}", dto.getVThd(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getVThd()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+
+        //相（线）电压基波有效值
+        pqReasonableRangeDto = map.get(DataCleanEnum.V_Data.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getV1() < (pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))
+                    || dto.getV1() > (pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()))) {
+                //log.info("dataV-基波电压数据异常,已清洗!数据值:{},数据时间:{}", dto.getV1(), dto.getMinTime());
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getV1()
+                        ,pqReasonableRangeDto.getMinValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel())
+                        ,pqReasonableRangeDto.getMaxValue()*DataCommonUtils.getVoltageData(line.getVoltageLevel()));
+                list.add(pqDataVerify);
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataI(Map<String, PqReasonableRangeDto> map, LineDetailVO.Detail line, DataIDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto;
+        List<String> phaseList;
+        //线电压有效值
+        pqReasonableRangeDto = map.get(DataCleanEnum.RmsI.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getRms() > line.getCT1()) {
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getRms()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,line.getCT1());
+                list.add(pqDataVerify);
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataPlt(Map<String, PqReasonableRangeDto> map, DataPltDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto;
+        List<String> phaseList;
+        //线电压有效值
+        pqReasonableRangeDto = map.get(DataCleanEnum.Plt.getCode());
+        phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getPlt() < pqReasonableRangeDto.getMinValue() || dto.getPlt() > pqReasonableRangeDto.getMaxValue()) {
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getPlt()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataInHarmV(Map<String, PqReasonableRangeDto> map, DataHarmDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto = map.get(DataCleanEnum.V_InHarm.getCode());
+        List<String> phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            // 50次谐波
+            for (int i = 1; i <= 50; i++) {
+                // 通过反射获取dto.getV(i)的值
+                double vValue = getVValue(dto, i);
+                if (vValue < pqReasonableRangeDto.getMinValue() || vValue > pqReasonableRangeDto.getMaxValue()) {
+                    PqDataVerify pqDataVerify = getPqDataVerify(
+                            dto.getLineId(),
+                            dto.getMinTime(),
+                            dto.getValueType(),
+                            dto.getPhasicType(),
+                            pqReasonableRangeDto.getIndexCode(),
+                            (i - 0.5) + pqReasonableRangeDto.getIndexName(),
+                            pqReasonableRangeDto.getInfluxdbTableName(),
+                            vValue,
+                            pqReasonableRangeDto.getMinValue(),
+                            pqReasonableRangeDto.getMaxValue()
+                    );
+                    list.add(pqDataVerify);
+                }
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataHarmRateV(Map<String, PqReasonableRangeDto> map, DataHarmDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto = map.get(DataCleanEnum.V_Rate.getCode());
+        List<String> phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            // 50次谐波
+            for (int i = 2; i <= 50; i++) {
+                // 通过反射获取dto.getV(i)的值
+                double vValue = getVValue(dto, i);
+                if (vValue < pqReasonableRangeDto.getMinValue() || vValue > pqReasonableRangeDto.getMaxValue()) {
+                    PqDataVerify pqDataVerify = getPqDataVerify(
+                            dto.getLineId(),
+                            dto.getMinTime(),
+                            dto.getValueType(),
+                            dto.getPhasicType(),
+                            pqReasonableRangeDto.getIndexCode(),
+                            i + pqReasonableRangeDto.getIndexName(),
+                            pqReasonableRangeDto.getInfluxdbTableName(),
+                            vValue,
+                            pqReasonableRangeDto.getMinValue(),
+                            pqReasonableRangeDto.getMaxValue()
+                    );
+                    list.add(pqDataVerify);
+                }
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataHarmPowerP(Map<String, PqReasonableRangeDto> map, DataPowerPDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto = map.get(DataCleanEnum.Pf.getCode());
+        List<String> phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getPf() < pqReasonableRangeDto.getMinValue() || dto.getPf() > pqReasonableRangeDto.getMaxValue()) {
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getPf()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataHarmPhasicV(Map<String, PqReasonableRangeDto> map, DataHarmDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto = map.get(DataCleanEnum.V.getCode());
+        List<String> phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            // 50次谐波
+            for (int i = 1; i <= 50; i++) {
+                // 通过反射获取dto.getV(i)的值
+                double vValue = getVValue(dto, i);
+                if (vValue < pqReasonableRangeDto.getMinValue() || vValue > pqReasonableRangeDto.getMaxValue()) {
+                    PqDataVerify pqDataVerify = getPqDataVerify(
+                            dto.getLineId(),
+                            dto.getMinTime(),
+                            dto.getValueType(),
+                            dto.getPhasicType(),
+                            pqReasonableRangeDto.getIndexCode(),
+                            i + pqReasonableRangeDto.getIndexName(),
+                            pqReasonableRangeDto.getInfluxdbTableName(),
+                            vValue,
+                            pqReasonableRangeDto.getMinValue(),
+                            pqReasonableRangeDto.getMaxValue()
+                    );
+                    list.add(pqDataVerify);
+                }
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataFluc(Map<String, PqReasonableRangeDto> map, DataFlucDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto = map.get(DataCleanEnum.Fluc.getCode());
+        List<String> phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getFluc() < pqReasonableRangeDto.getMinValue() || dto.getFluc() > pqReasonableRangeDto.getMaxValue()) {
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getFluc()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+        return list;
+    }
+
+    /**
+     * 获取数据的标准范围，进行数据比对
+     */
+    public List<PqDataVerify> judgeDataFlicker(Map<String, PqReasonableRangeDto> map, DataFlickerDto dto) {
+        List<PqDataVerify> list = new ArrayList<>();
+        PqReasonableRangeDto pqReasonableRangeDto = map.get(DataCleanEnum.Pst.getCode());
+        List<String> phaseList = Arrays.asList(pqReasonableRangeDto.getPhaseType().split(","));
+        if (phaseList.contains(dto.getPhasicType())) {
+            if (dto.getPst() < pqReasonableRangeDto.getMinValue() || dto.getPst() > pqReasonableRangeDto.getMaxValue()) {
+                PqDataVerify pqDataVerify = getPqDataVerify(dto.getLineId()
+                        ,dto.getMinTime()
+                        ,dto.getValueType()
+                        ,dto.getPhasicType()
+                        ,pqReasonableRangeDto.getIndexCode()
+                        ,pqReasonableRangeDto.getIndexName()
+                        ,pqReasonableRangeDto.getInfluxdbTableName()
+                        ,dto.getPst()
+                        ,pqReasonableRangeDto.getMinValue()
+                        ,pqReasonableRangeDto.getMaxValue());
+                list.add(pqDataVerify);
+            }
+        }
+        return list;
+    }
+
+
+    public PqDataVerify getPqDataVerify(String lineId,String time,String valueType, String phasicType, String indexCode, String indexName, String indexTable, Double data, Double minValue, Double maxValue) {
+        PqDataVerify pqDataVerify = new PqDataVerify();
+        pqDataVerify.setLineId(lineId);
+        pqDataVerify.setTime(TimeUtils.StringToLocalDateTime(time));
+        pqDataVerify.setValueType(valueType);
+        pqDataVerify.setPhasicType(phasicType);
+        pqDataVerify.setIndexCode(indexCode);
+        pqDataVerify.setIndexName(indexName);
+        pqDataVerify.setIndexTable(indexTable);
+        //这里对数据进行判断，如果值过大，都超出数据库存储范围会报错，无法插入，所以这里设置门槛 上下限都为1千万
+        if (data > 10000000.0) {
+            pqDataVerify.setAbnormalValue(9999999.0);
+        } else if (data < -10000000.0) {
+            pqDataVerify.setAbnormalValue(-9999999.0);
+        } else {
+            pqDataVerify.setAbnormalValue(data);
+        }
+        pqDataVerify.setMinValue(minValue);
+        pqDataVerify.setMaxValue(maxValue);
+        return pqDataVerify;
+    }
+
+    private double getVValue(DataHarmDto dto, int index) {
+        try {
+            Method method = DataHarmDto.class.getMethod("getV" + index);
+            return (double) method.invoke(dto);
+        } catch (Exception e) {
+            throw new RuntimeException("Failed to get V value for index: " + index, e);
+        }
+    }
+
 }

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/serviceimpl/line/DayDataServiceImpl.java

@@ -4,9 +4,12 @@ import cn.hutool.core.collection.CollUtil;
 import com.njcn.algorithm.pojo.bo.CalculatedParam;
 import com.njcn.algorithm.service.line.IDayDataService;
 import com.njcn.dataProcess.api.DataVFeignClient;
+import com.njcn.dataProcess.api.PqDataVerifyFeignClient;
+import com.njcn.dataProcess.enums.DataCleanEnum;
 import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.pojo.dto.CommonMinuteDto;
 import com.njcn.dataProcess.pojo.dto.DataVDto;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
 import com.njcn.dataProcess.util.TimeUtils;
 import com.njcn.influx.constant.InfluxDbSqlConstant;
 import lombok.RequiredArgsConstructor;
@@ -19,6 +22,7 @@ import org.springframework.stereotype.Component;
 import javax.annotation.Resource;
 import java.time.LocalDateTime;
 import java.util.*;
+import java.util.stream.Collectors;
 
 /**
  * @author xy
@@ -32,10 +36,12 @@ public class DayDataServiceImpl implements IDayDataService {
     private final static Integer NUM = 100;
     @Resource
     private DataVFeignClient dataVFeignClient;
+    @Resource
+    private PqDataVerifyFeignClient pqDataVerifyFeignClient;
 
     @Override
     public void dataVHandler(CalculatedParam calculatedParam) {
-        logger.info("{},dataV表转r_stat_data_v_d开始=====》", LocalDateTime.now());
+        logger.info("{},dataV表转r_stat_data_v_d算法开始=====》", LocalDateTime.now());
         List<DataVDto> result = new ArrayList<>();
         //远程接口获取分钟数据
         LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
@@ -45,6 +51,9 @@ public class DayDataServiceImpl implements IDayDataService {
         List<List<String>> pendingIds =  ListUtils.partition(calculatedParam.getIdList(),NUM);
         pendingIds.forEach(list->{
             lineParam.setLineId(list);
+            //添加异常数据时间点
+            getAbnormalData(lineParam);
+            //获取原始数据
             List<CommonMinuteDto> partList = dataVFeignClient.getBaseData(lineParam).getData();
             if (CollUtil.isNotEmpty(partList)) {
                 partList.forEach(item->{
@@ -61,7 +70,7 @@ public class DayDataServiceImpl implements IDayDataService {
                             dto.setLineId(item.getLineId());
                             dto.setPhasicType(item2.getPhasicType());
                             dto.setValueType(item3.getValueType());
-                            dto.setQualityFlag("0");
+                            dto.setQualityFlag(item.getQualityFlag());
                             channelDataVHandler(item3,valueTypes,dto,true);
                             result.add(dto);
                         });
@@ -75,87 +84,103 @@ public class DayDataServiceImpl implements IDayDataService {
         }
     }
 
+    //获取异常数据集合
+    public void getAbnormalData(LineCountEvaluateParam lineParam) {
+        lineParam.setTableName(DataCleanEnum.DataV.getCode());
+        // 获取异常数据，用于排除异常数据
+        List<PqDataVerify> pqDataVerifies = pqDataVerifyFeignClient.queryData(lineParam).getData();
+        if (CollUtil.isNotEmpty(pqDataVerifies)) {
+            Map<String, List<String>> timeMap = pqDataVerifies.stream()
+                    .collect(Collectors.groupingBy(
+                            PqDataVerify::getLineId,
+                            Collectors.mapping(item->TimeUtils.LocalDateTimeToString(item.getTime()), Collectors.toList())
+                    ));
+            lineParam.setAbnormalTime(timeMap);
+        }
+    }
 
     //指标处理
     //pojo1 为正常数据集合
     //pojo2 为平均值数据集合，根据不同情况用来计算cp95
     public void channelDataVHandler(CommonMinuteDto.ValueType pojo1, CommonMinuteDto.ValueType pojo2, DataVDto dto, boolean scheme) {
         CommonMinuteDto.ValueType valueType;
+        String type;
         if (dto.getValueType().equalsIgnoreCase(InfluxDbSqlConstant.CP95) && !scheme) {
             valueType = pojo2;
+            type = "CP95";
         } else {
             valueType = pojo1;
+            type = pojo1.getValueType();
         }
         //按照指标集合排列顺序取值
-        dto.setFreq(getData(valueType.getValueType(),valueType.getValueList().get(0),scheme));
-        dto.setFreqDev(getData(valueType.getValueType(),valueType.getValueList().get(1),scheme));
-        dto.setRms(getData(valueType.getValueType(),valueType.getValueList().get(2),scheme));
-        dto.setRmsLvr(getData(valueType.getValueType(),valueType.getValueList().get(3),scheme));
-        dto.setVNeg(getData(valueType.getValueType(),valueType.getValueList().get(4),scheme));
-        dto.setVPos(getData(valueType.getValueType(),valueType.getValueList().get(5),scheme));
-        dto.setVThd(getData(valueType.getValueType(),valueType.getValueList().get(6),scheme));
-        dto.setVUnbalance(getData(valueType.getValueType(),valueType.getValueList().get(7),scheme));
-        dto.setVZero(getData(valueType.getValueType(),valueType.getValueList().get(8),scheme));
-        dto.setVlDev(getData(valueType.getValueType(),valueType.getValueList().get(9),scheme));
-        dto.setVuDev(getData(valueType.getValueType(),valueType.getValueList().get(10),scheme));
+        dto.setFreq(getData(type,valueType.getValueList().get(0),scheme));
+        dto.setFreqDev(getData(type,valueType.getValueList().get(1),scheme));
+        dto.setRms(getData(type,valueType.getValueList().get(2),scheme));
+        dto.setRmsLvr(getData(type,valueType.getValueList().get(3),scheme));
+        dto.setVNeg(getData(type,valueType.getValueList().get(4),scheme));
+        dto.setVPos(getData(type,valueType.getValueList().get(5),scheme));
+        dto.setVThd(getData(type,valueType.getValueList().get(6),scheme));
+        dto.setVUnbalance(getData(type,valueType.getValueList().get(7),scheme));
+        dto.setVZero(getData(type,valueType.getValueList().get(8),scheme));
+        dto.setVlDev(getData(type,valueType.getValueList().get(9),scheme));
+        dto.setVuDev(getData(type,valueType.getValueList().get(10),scheme));
 
-        dto.setV1(getData(valueType.getValueType(),valueType.getValueList().get(11),scheme));
-        dto.setV2(getData(valueType.getValueType(),valueType.getValueList().get(12),scheme));
-        dto.setV3(getData(valueType.getValueType(),valueType.getValueList().get(13),scheme));
-        dto.setV4(getData(valueType.getValueType(),valueType.getValueList().get(14),scheme));
-        dto.setV5(getData(valueType.getValueType(),valueType.getValueList().get(15),scheme));
-        dto.setV6(getData(valueType.getValueType(),valueType.getValueList().get(16),scheme));
-        dto.setV7(getData(valueType.getValueType(),valueType.getValueList().get(17),scheme));
-        dto.setV8(getData(valueType.getValueType(),valueType.getValueList().get(18),scheme));
-        dto.setV9(getData(valueType.getValueType(),valueType.getValueList().get(19),scheme));
-        dto.setV10(getData(valueType.getValueType(),valueType.getValueList().get(20),scheme));
+        dto.setV1(getData(type,valueType.getValueList().get(11),scheme));
+        dto.setV2(getData(type,valueType.getValueList().get(12),scheme));
+        dto.setV3(getData(type,valueType.getValueList().get(13),scheme));
+        dto.setV4(getData(type,valueType.getValueList().get(14),scheme));
+        dto.setV5(getData(type,valueType.getValueList().get(15),scheme));
+        dto.setV6(getData(type,valueType.getValueList().get(16),scheme));
+        dto.setV7(getData(type,valueType.getValueList().get(17),scheme));
+        dto.setV8(getData(type,valueType.getValueList().get(18),scheme));
+        dto.setV9(getData(type,valueType.getValueList().get(19),scheme));
+        dto.setV10(getData(type,valueType.getValueList().get(20),scheme));
 
-        dto.setV11(getData(valueType.getValueType(),valueType.getValueList().get(21),scheme));
-        dto.setV12(getData(valueType.getValueType(),valueType.getValueList().get(22),scheme));
-        dto.setV13(getData(valueType.getValueType(),valueType.getValueList().get(23),scheme));
-        dto.setV14(getData(valueType.getValueType(),valueType.getValueList().get(24),scheme));
-        dto.setV15(getData(valueType.getValueType(),valueType.getValueList().get(25),scheme));
-        dto.setV16(getData(valueType.getValueType(),valueType.getValueList().get(26),scheme));
-        dto.setV17(getData(valueType.getValueType(),valueType.getValueList().get(27),scheme));
-        dto.setV18(getData(valueType.getValueType(),valueType.getValueList().get(28),scheme));
-        dto.setV19(getData(valueType.getValueType(),valueType.getValueList().get(29),scheme));
-        dto.setV20(getData(valueType.getValueType(),valueType.getValueList().get(30),scheme));
+        dto.setV11(getData(type,valueType.getValueList().get(21),scheme));
+        dto.setV12(getData(type,valueType.getValueList().get(22),scheme));
+        dto.setV13(getData(type,valueType.getValueList().get(23),scheme));
+        dto.setV14(getData(type,valueType.getValueList().get(24),scheme));
+        dto.setV15(getData(type,valueType.getValueList().get(25),scheme));
+        dto.setV16(getData(type,valueType.getValueList().get(26),scheme));
+        dto.setV17(getData(type,valueType.getValueList().get(27),scheme));
+        dto.setV18(getData(type,valueType.getValueList().get(28),scheme));
+        dto.setV19(getData(type,valueType.getValueList().get(29),scheme));
+        dto.setV20(getData(type,valueType.getValueList().get(30),scheme));
 
-        dto.setV21(getData(valueType.getValueType(),valueType.getValueList().get(31),scheme));
-        dto.setV22(getData(valueType.getValueType(),valueType.getValueList().get(32),scheme));
-        dto.setV23(getData(valueType.getValueType(),valueType.getValueList().get(33),scheme));
-        dto.setV24(getData(valueType.getValueType(),valueType.getValueList().get(34),scheme));
-        dto.setV25(getData(valueType.getValueType(),valueType.getValueList().get(35),scheme));
-        dto.setV26(getData(valueType.getValueType(),valueType.getValueList().get(36),scheme));
-        dto.setV27(getData(valueType.getValueType(),valueType.getValueList().get(37),scheme));
-        dto.setV28(getData(valueType.getValueType(),valueType.getValueList().get(38),scheme));
-        dto.setV29(getData(valueType.getValueType(),valueType.getValueList().get(39),scheme));
-        dto.setV30(getData(valueType.getValueType(),valueType.getValueList().get(40),scheme));
+        dto.setV21(getData(type,valueType.getValueList().get(31),scheme));
+        dto.setV22(getData(type,valueType.getValueList().get(32),scheme));
+        dto.setV23(getData(type,valueType.getValueList().get(33),scheme));
+        dto.setV24(getData(type,valueType.getValueList().get(34),scheme));
+        dto.setV25(getData(type,valueType.getValueList().get(35),scheme));
+        dto.setV26(getData(type,valueType.getValueList().get(36),scheme));
+        dto.setV27(getData(type,valueType.getValueList().get(37),scheme));
+        dto.setV28(getData(type,valueType.getValueList().get(38),scheme));
+        dto.setV29(getData(type,valueType.getValueList().get(39),scheme));
+        dto.setV30(getData(type,valueType.getValueList().get(40),scheme));
 
-        dto.setV31(getData(valueType.getValueType(),valueType.getValueList().get(41),scheme));
-        dto.setV32(getData(valueType.getValueType(),valueType.getValueList().get(42),scheme));
-        dto.setV33(getData(valueType.getValueType(),valueType.getValueList().get(43),scheme));
-        dto.setV34(getData(valueType.getValueType(),valueType.getValueList().get(44),scheme));
-        dto.setV35(getData(valueType.getValueType(),valueType.getValueList().get(45),scheme));
-        dto.setV36(getData(valueType.getValueType(),valueType.getValueList().get(46),scheme));
-        dto.setV37(getData(valueType.getValueType(),valueType.getValueList().get(47),scheme));
-        dto.setV38(getData(valueType.getValueType(),valueType.getValueList().get(48),scheme));
-        dto.setV39(getData(valueType.getValueType(),valueType.getValueList().get(49),scheme));
-        dto.setV40(getData(valueType.getValueType(),valueType.getValueList().get(50),scheme));
+        dto.setV31(getData(type,valueType.getValueList().get(41),scheme));
+        dto.setV32(getData(type,valueType.getValueList().get(42),scheme));
+        dto.setV33(getData(type,valueType.getValueList().get(43),scheme));
+        dto.setV34(getData(type,valueType.getValueList().get(44),scheme));
+        dto.setV35(getData(type,valueType.getValueList().get(45),scheme));
+        dto.setV36(getData(type,valueType.getValueList().get(46),scheme));
+        dto.setV37(getData(type,valueType.getValueList().get(47),scheme));
+        dto.setV38(getData(type,valueType.getValueList().get(48),scheme));
+        dto.setV39(getData(type,valueType.getValueList().get(49),scheme));
+        dto.setV40(getData(type,valueType.getValueList().get(50),scheme));
 
-        dto.setV41(getData(valueType.getValueType(),valueType.getValueList().get(51),scheme));
-        dto.setV42(getData(valueType.getValueType(),valueType.getValueList().get(52),scheme));
-        dto.setV43(getData(valueType.getValueType(),valueType.getValueList().get(53),scheme));
-        dto.setV44(getData(valueType.getValueType(),valueType.getValueList().get(54),scheme));
-        dto.setV45(getData(valueType.getValueType(),valueType.getValueList().get(55),scheme));
-        dto.setV46(getData(valueType.getValueType(),valueType.getValueList().get(56),scheme));
-        dto.setV47(getData(valueType.getValueType(),valueType.getValueList().get(57),scheme));
-        dto.setV48(getData(valueType.getValueType(),valueType.getValueList().get(58),scheme));
-        dto.setV49(getData(valueType.getValueType(),valueType.getValueList().get(59),scheme));
-        dto.setV50(getData(valueType.getValueType(),valueType.getValueList().get(60),scheme));
+        dto.setV41(getData(type,valueType.getValueList().get(51),scheme));
+        dto.setV42(getData(type,valueType.getValueList().get(52),scheme));
+        dto.setV43(getData(type,valueType.getValueList().get(53),scheme));
+        dto.setV44(getData(type,valueType.getValueList().get(54),scheme));
+        dto.setV45(getData(type,valueType.getValueList().get(55),scheme));
+        dto.setV46(getData(type,valueType.getValueList().get(56),scheme));
+        dto.setV47(getData(type,valueType.getValueList().get(57),scheme));
+        dto.setV48(getData(type,valueType.getValueList().get(58),scheme));
+        dto.setV49(getData(type,valueType.getValueList().get(59),scheme));
+        dto.setV50(getData(type,valueType.getValueList().get(60),scheme));
     }
 
-
     //数据类型处理
     //cp95值的计算有点区别，会用到cp95的集合或者平均值的集合
     public Double getData(String valueType, List<Double> list, boolean scheme) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataFlickerFeignClient.java

@@ -2,9 +2,10 @@ package com.njcn.dataProcess.api;
 
 import com.njcn.common.pojo.constant.ServerInfo;
 import com.njcn.common.pojo.response.HttpResult;
-
 import com.njcn.dataProcess.api.fallback.DataFlickerFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataFlickerDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlickerDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -24,4 +25,6 @@ public interface DataFlickerFeignClient {
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataFlickerDTO> dataFlickerDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataFlickerDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataFlucFeignClient.java

@@ -2,9 +2,10 @@ package com.njcn.dataProcess.api;
 
 import com.njcn.common.pojo.constant.ServerInfo;
 import com.njcn.common.pojo.response.HttpResult;
-
 import com.njcn.dataProcess.api.fallback.DataFlucFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataFlucDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlucDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -24,4 +25,6 @@ public interface DataFlucFeignClient {
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataFlucDTO> dataFlucDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataFlucDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataHarmRateVFeignClient.java

@@ -0,0 +1,23 @@
+package com.njcn.dataProcess.api;
+
+import com.njcn.common.pojo.constant.ServerInfo;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.fallback.DataHarmRateVFeignClientFallbackFactory;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+import org.springframework.cloud.openfeign.FeignClient;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+
+import java.util.List;
+
+/**
+ * @author xy
+ */
+@FeignClient(value =  ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/dataHarmRateV", fallbackFactory = DataHarmRateVFeignClientFallbackFactory.class, contextId = "dataHarmRateV")
+public interface DataHarmRateVFeignClient {
+
+    @PostMapping("/getRawData")
+    HttpResult<List<DataHarmDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataHarmphasicVFeignClient.java

@@ -2,9 +2,10 @@ package com.njcn.dataProcess.api;
 
 import com.njcn.common.pojo.constant.ServerInfo;
 import com.njcn.common.pojo.response.HttpResult;
-
-import com.njcn.dataProcess.api.fallback.DataIFeignClientFallbackFactory;
+import com.njcn.dataProcess.api.fallback.DataHarmphasicVFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -16,7 +17,7 @@ import java.util.List;
  * @version 1.0.0
  * @date 2022年01月05日 15:11
  */
-@FeignClient(value =  ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/dataHarmphasicV", fallbackFactory = DataIFeignClientFallbackFactory.class, contextId = "dataHarmphasicV")
+@FeignClient(value =  ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/dataHarmphasicV", fallbackFactory = DataHarmphasicVFeignClientFallbackFactory.class, contextId = "dataHarmphasicV")
 public interface DataHarmphasicVFeignClient {
 
 
@@ -24,4 +25,7 @@ public interface DataHarmphasicVFeignClient {
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataHarmphasicVDTO> dataHarmphasicVDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataHarmDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
+
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataHarmpowerPFeignClient.java

@@ -2,9 +2,10 @@ package com.njcn.dataProcess.api;
 
 import com.njcn.common.pojo.constant.ServerInfo;
 import com.njcn.common.pojo.response.HttpResult;
-
 import com.njcn.dataProcess.api.fallback.DataHarmpowerPFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataPowerPDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -19,9 +20,9 @@ import java.util.List;
 @FeignClient(value = ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/dataHarmpowerP", fallbackFactory = DataHarmpowerPFeignClientFallbackFactory.class, contextId = "dataHarmpowerP")
 public interface DataHarmpowerPFeignClient {
 
-
-
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataHarmpowerPDTO> dataHarmpowerPDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataPowerPDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataIFeignClient.java

@@ -2,9 +2,10 @@ package com.njcn.dataProcess.api;
 
 import com.njcn.common.pojo.constant.ServerInfo;
 import com.njcn.common.pojo.response.HttpResult;
-
 import com.njcn.dataProcess.api.fallback.DataIFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataIDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -19,9 +20,10 @@ import java.util.List;
 @FeignClient(value =  ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/dataI", fallbackFactory = DataIFeignClientFallbackFactory.class, contextId = "dataI")
 public interface DataIFeignClient {
 
-
-
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataIDTO> dataIDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataIDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
+
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataInharmVFeignClient.java

@@ -5,6 +5,8 @@ import com.njcn.common.pojo.response.HttpResult;
 
 import com.njcn.dataProcess.api.fallback.DataInharmVFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataInharmVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -24,4 +26,7 @@ public interface DataInharmVFeignClient {
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataInharmVDTO> dataInharmVDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataHarmDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
+
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/DataPltFeignClient.java

@@ -2,9 +2,10 @@ package com.njcn.dataProcess.api;
 
 import com.njcn.common.pojo.constant.ServerInfo;
 import com.njcn.common.pojo.response.HttpResult;
-
 import com.njcn.dataProcess.api.fallback.DataPltFeignClientFallbackFactory;
 import com.njcn.dataProcess.dto.DataPltDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 import org.springframework.cloud.openfeign.FeignClient;
 import org.springframework.web.bind.annotation.PostMapping;
 import org.springframework.web.bind.annotation.RequestBody;
@@ -24,4 +25,7 @@ public interface DataPltFeignClient {
     @PostMapping("/batchInsertion")
     HttpResult<String> batchInsertion(@RequestBody List<DataPltDTO> dataPltDTOList);
 
+    @PostMapping("/getRawData")
+    HttpResult<List<DataPltDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam);
+
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/PqDataVerifyFeignClient.java

@@ -0,0 +1,34 @@
+package com.njcn.dataProcess.api;
+
+import com.njcn.common.pojo.constant.ServerInfo;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.fallback.PqDataVerifyFeignClientFallbackFactory;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+import io.swagger.annotations.ApiOperation;
+import org.springframework.cloud.openfeign.FeignClient;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+
+import java.util.List;
+
+/**
+ * @author xy
+ * @version 1.0.0
+ * @date 2025年02月13日 20:11
+ */
+@FeignClient(value =  ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/pqDataVerify", fallbackFactory = PqDataVerifyFeignClientFallbackFactory.class, contextId = "pqDataVerify")
+public interface PqDataVerifyFeignClient {
+
+    @PostMapping("/insertData")
+    @ApiOperation("存储清洗的异常数据")
+    HttpResult<List<PqDataVerify>> insertData(@RequestBody List<PqDataVerify> list);
+
+    @PostMapping("/queryData")
+    @ApiOperation("查询清洗的异常数据")
+    HttpResult<List<PqDataVerify>> queryData(@RequestBody LineCountEvaluateParam param);
+
+
+
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/PqReasonableRangeFeignClient.java

@@ -0,0 +1,27 @@
+package com.njcn.dataProcess.api;
+
+import com.njcn.common.pojo.constant.ServerInfo;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.fallback.PqReasonableRangeFeignClientFallbackFactory;
+import com.njcn.dataProcess.param.DataCleanParam;
+import com.njcn.dataProcess.pojo.dto.PqReasonableRangeDto;
+import io.swagger.annotations.ApiOperation;
+import org.springframework.cloud.openfeign.FeignClient;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+
+import java.util.List;
+
+/**
+ * @author xy
+ * @version 1.0.0
+ * @date 2025年02月13日 20:11
+ */
+@FeignClient(value =  ServerInfo.PLATFORM_DATA_PROCESSING_BOOT, path = "/pqReasonableRange", fallbackFactory = PqReasonableRangeFeignClientFallbackFactory.class, contextId = "pqReasonableRange")
+public interface PqReasonableRangeFeignClient {
+
+    @PostMapping("/getData")
+    @ApiOperation("按条件获取数据合理范围")
+    HttpResult<List<PqReasonableRangeDto>> getData(@RequestBody DataCleanParam param);
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataFlickerFeignClientFallbackFactory.java

@@ -6,6 +6,8 @@ import com.njcn.common.pojo.response.HttpResult;
 
 import com.njcn.dataProcess.api.DataFlickerFeignClient;
 import com.njcn.dataProcess.dto.DataFlickerDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlickerDto;
 import com.njcn.dataProcess.util.DataProcessingEnumUtil;
 import feign.hystrix.FallbackFactory;
 import lombok.extern.slf4j.Slf4j;
@@ -44,6 +46,12 @@ public class DataFlickerFeignClientFallbackFactory implements FallbackFactory<Da
                 throw new BusinessException(finalExceptionEnum);
             }
 
+            @Override
+            public HttpResult<List<DataFlickerDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
         };
     }
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataFlucFeignClientFallbackFactory.java

@@ -3,9 +3,10 @@ package com.njcn.dataProcess.api.fallback;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.exception.BusinessException;
 import com.njcn.common.pojo.response.HttpResult;
-
 import com.njcn.dataProcess.api.DataFlucFeignClient;
 import com.njcn.dataProcess.dto.DataFlucDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlucDto;
 import com.njcn.dataProcess.util.DataProcessingEnumUtil;
 import feign.hystrix.FallbackFactory;
 import lombok.extern.slf4j.Slf4j;
@@ -40,10 +41,17 @@ public class DataFlucFeignClientFallbackFactory implements FallbackFactory<DataF
 
             @Override
             public HttpResult<String> batchInsertion(List<DataFlucDTO> dataFlucDTOList) {
+
                 log.error("{}异常，降级处理，异常为：{}","批量插入数据",cause.toString());
                 throw new BusinessException(finalExceptionEnum);
             }
 
+            @Override
+            public HttpResult<List<DataFlucDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
         };
     }
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataHarmRateVFeignClientFallbackFactory.java

@@ -0,0 +1,46 @@
+package com.njcn.dataProcess.api.fallback;
+
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.exception.BusinessException;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.DataHarmRateVFeignClient;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+import com.njcn.dataProcess.util.DataProcessingEnumUtil;
+import feign.hystrix.FallbackFactory;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+
+/**
+ * @author xy
+ */
+@Slf4j
+@Component
+public class DataHarmRateVFeignClientFallbackFactory implements FallbackFactory<DataHarmRateVFeignClient> {
+
+    /**
+     * 输出远程请求接口异常日志
+     * @param cause RPC请求异常
+     */
+    @Override
+    public DataHarmRateVFeignClient create(Throwable cause) {
+        //判断抛出异常是否为解码器抛出的业务异常
+        Enum<?> exceptionEnum = CommonResponseEnum.SERVICE_FALLBACK;
+        if(cause.getCause() instanceof BusinessException){
+            BusinessException businessException = (BusinessException) cause.getCause();
+            exceptionEnum = DataProcessingEnumUtil.getExceptionEnum(businessException.getResult());
+        }
+        Enum<?> finalExceptionEnum = exceptionEnum;
+        return new DataHarmRateVFeignClient() {
+
+            @Override
+            public HttpResult<List<DataHarmDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
+        };
+    }
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataHarmphasicVFeignClientFallbackFactory.java

@@ -0,0 +1,56 @@
+package com.njcn.dataProcess.api.fallback;
+
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.exception.BusinessException;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.DataHarmphasicVFeignClient;
+import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+import com.njcn.dataProcess.util.DataProcessingEnumUtil;
+import feign.hystrix.FallbackFactory;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+
+/**
+ * @author denghuajun
+ * @version 1.0.0
+ * @date 2022年01月05日 15:08
+ */
+@Slf4j
+@Component
+public class DataHarmphasicVFeignClientFallbackFactory implements FallbackFactory<DataHarmphasicVFeignClient> {
+
+
+    /**
+     * 输出远程请求接口异常日志
+     * @param cause RPC请求异常
+     */
+    @Override
+    public DataHarmphasicVFeignClient create(Throwable cause) {
+        //判断抛出异常是否为解码器抛出的业务异常
+        Enum<?> exceptionEnum = CommonResponseEnum.SERVICE_FALLBACK;
+        if(cause.getCause() instanceof BusinessException){
+            BusinessException businessException = (BusinessException) cause.getCause();
+            exceptionEnum = DataProcessingEnumUtil.getExceptionEnum(businessException.getResult());
+        }
+        Enum<?> finalExceptionEnum = exceptionEnum;
+        return new DataHarmphasicVFeignClient() {
+
+            @Override
+            public HttpResult<String> batchInsertion(List<DataHarmphasicVDTO> dataHarmphasicVDTOList) {
+                log.error("{}异常，降级处理，异常为：{}","批量插入数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
+            @Override
+            public HttpResult<List<DataHarmDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
+        };
+    }
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataHarmpowerPFeignClientFallbackFactory.java

@@ -5,6 +5,8 @@ import com.njcn.common.pojo.exception.BusinessException;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.dataProcess.api.DataHarmpowerPFeignClient;
 import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataPowerPDto;
 import com.njcn.dataProcess.util.DataProcessingEnumUtil;
 import feign.hystrix.FallbackFactory;
 import lombok.extern.slf4j.Slf4j;
@@ -43,6 +45,12 @@ public class DataHarmpowerPFeignClientFallbackFactory implements FallbackFactory
                 throw new BusinessException(finalExceptionEnum);
             }
 
+            @Override
+            public HttpResult<List<DataPowerPDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
         };
     }
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataIFeignClientFallbackFactory.java

@@ -5,6 +5,8 @@ import com.njcn.common.pojo.exception.BusinessException;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.dataProcess.api.DataIFeignClient;
 import com.njcn.dataProcess.dto.DataIDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
 import com.njcn.dataProcess.util.DataProcessingEnumUtil;
 import com.njcn.system.utils.SystemEnumUtil;
 import feign.hystrix.FallbackFactory;
@@ -44,6 +46,12 @@ public class DataIFeignClientFallbackFactory implements FallbackFactory<DataIFei
                 throw new BusinessException(finalExceptionEnum);
             }
 
+            @Override
+            public HttpResult<List<DataIDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
         };
     }
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataInharmVFeignClientFallbackFactory.java

@@ -5,8 +5,9 @@ import com.njcn.common.pojo.exception.BusinessException;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.dataProcess.api.DataInharmVFeignClient;
 import com.njcn.dataProcess.dto.DataInharmVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.util.DataProcessingEnumUtil;
-import com.njcn.system.utils.SystemEnumUtil;
 import feign.hystrix.FallbackFactory;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.stereotype.Component;
@@ -44,6 +45,12 @@ public class DataInharmVFeignClientFallbackFactory implements FallbackFactory<Da
                 throw new BusinessException(finalExceptionEnum);
             }
 
+            @Override
+            public HttpResult<List<DataHarmDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
         };
     }
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/DataPltFeignClientFallbackFactory.java

@@ -5,8 +5,9 @@ import com.njcn.common.pojo.exception.BusinessException;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.dataProcess.api.DataPltFeignClient;
 import com.njcn.dataProcess.dto.DataPltDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 import com.njcn.dataProcess.util.DataProcessingEnumUtil;
-import com.njcn.system.utils.SystemEnumUtil;
 import feign.hystrix.FallbackFactory;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.stereotype.Component;
@@ -44,6 +45,12 @@ public class DataPltFeignClientFallbackFactory implements FallbackFactory<DataPl
                 throw new BusinessException(finalExceptionEnum);
             }
 
+            @Override
+            public HttpResult<List<DataPltDto>> getRawData(LineCountEvaluateParam lineParam) {
+                log.error("{}异常，降级处理，异常为：{}","获取原始数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
         };
     }
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/PqDataVerifyFeignClientFallbackFactory.java

@@ -0,0 +1,53 @@
+package com.njcn.dataProcess.api.fallback;
+
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.exception.BusinessException;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.PqDataVerifyFeignClient;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+import com.njcn.dataProcess.util.DataProcessingEnumUtil;
+import feign.hystrix.FallbackFactory;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+
+/**
+ * @author xy
+ * @version 1.0.0
+ * @date 2025年02月13日 20:13
+ */
+@Slf4j
+@Component
+public class PqDataVerifyFeignClientFallbackFactory implements FallbackFactory<PqDataVerifyFeignClient> {
+
+    /**
+     * 输出远程请求接口异常日志
+     * @param cause RPC请求异常
+     */
+    @Override
+    public PqDataVerifyFeignClient create(Throwable cause) {
+        //判断抛出异常是否为解码器抛出的业务异常
+        Enum<?> exceptionEnum = CommonResponseEnum.SERVICE_FALLBACK;
+        if(cause.getCause() instanceof BusinessException){
+            BusinessException businessException = (BusinessException) cause.getCause();
+            exceptionEnum = DataProcessingEnumUtil.getExceptionEnum(businessException.getResult());
+        }
+        Enum<?> finalExceptionEnum = exceptionEnum;
+        return new PqDataVerifyFeignClient() {
+
+            @Override
+            public HttpResult<List<PqDataVerify>> insertData(List<PqDataVerify> list) {
+                log.error("{}异常，降级处理，异常为：{}","存储清洗的异常数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+
+            @Override
+            public HttpResult<List<PqDataVerify>> queryData(LineCountEvaluateParam param) {
+                log.error("{}异常，降级处理，异常为：{}","查询清洗的异常数据",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+        };
+    }
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/api/fallback/PqReasonableRangeFeignClientFallbackFactory.java

@@ -0,0 +1,47 @@
+package com.njcn.dataProcess.api.fallback;
+
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.exception.BusinessException;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.dataProcess.api.PqReasonableRangeFeignClient;
+import com.njcn.dataProcess.param.DataCleanParam;
+import com.njcn.dataProcess.pojo.dto.PqReasonableRangeDto;
+import com.njcn.dataProcess.util.DataProcessingEnumUtil;
+import feign.hystrix.FallbackFactory;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+
+/**
+ * @author xy
+ * @version 1.0.0
+ * @date 2025年02月13日 20:13
+ */
+@Slf4j
+@Component
+public class PqReasonableRangeFeignClientFallbackFactory implements FallbackFactory<PqReasonableRangeFeignClient> {
+
+    /**
+     * 输出远程请求接口异常日志
+     * @param cause RPC请求异常
+     */
+    @Override
+    public PqReasonableRangeFeignClient create(Throwable cause) {
+        //判断抛出异常是否为解码器抛出的业务异常
+        Enum<?> exceptionEnum = CommonResponseEnum.SERVICE_FALLBACK;
+        if(cause.getCause() instanceof BusinessException){
+            BusinessException businessException = (BusinessException) cause.getCause();
+            exceptionEnum = DataProcessingEnumUtil.getExceptionEnum(businessException.getResult());
+        }
+        Enum<?> finalExceptionEnum = exceptionEnum;
+        return new PqReasonableRangeFeignClient() {
+
+            @Override
+            public HttpResult<List<PqReasonableRangeDto>> getData(DataCleanParam param) {
+                log.error("{}异常，降级处理，异常为：{}","按条件获取数据合理范围",cause.toString());
+                throw new BusinessException(finalExceptionEnum);
+            }
+        };
+    }
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/enums/DataCleanEnum.java

@@ -0,0 +1,94 @@
+package com.njcn.dataProcess.enums;
+
+import lombok.Getter;
+
+/**
+ * 数据清洗枚举值
+ *
+ * @author xy
+ * @version 1.0
+ * @data 2025/2/13 15:08
+ */
+@Getter
+public enum DataCleanEnum {
+
+    /**
+     * 所属系统
+     */
+    Pqs("pqs","数据中心"),
+    Govern("govern","治理"),
+
+    /**
+     * 数据来源
+     */
+    InfluxDB("InfluxDB","时序数据库"),
+    MySql("MySql","关系型数据库"),
+
+    /**
+     * 数据表名
+     */
+    DataV("DataV","电压表"),
+    DataHarmPhasicV("DataHarmPhasicV","谐波电压相角表"),
+    DataI("DataI","电路表"),
+    DataFlicker("DataFlicker","短闪表"),
+    DataPlt("DataPlt","长闪表"),
+    DataFluc("DataFluc","电压波动"),
+    DataInHarmV("DataInHarmV","间谐波电压含有率表"),
+    DataHarmRateV("DataHarmRateV","谐波电压含有率表"),
+    DataHarmPowerP("DataHarmPowerP","功率因数表"),
+    RMpEventDetail("r_mp_event_detail","暂降表"),
+
+    /**
+     * 指标名称
+     */
+    //DataFlicker
+    Pst("pst","短时闪变"),
+
+    //DataFluc
+    Fluc("fluc","电压波动"),
+
+    //DataHarmPhasicV
+    V("v","次谐波电压基波相角"),
+
+    //DataHarmRateV
+    V_Rate("v","次谐波电压含有率"),
+
+    //DataHarmPowerP
+    Pf("pf","视在功率因素"),
+
+    //DataI
+    RmsI("rms","电流有效值"),
+
+    //DataInHarmV
+    V_InHarm("v","次间谐波电压含有率"),
+
+    //DataPlt
+    Plt("plt","长时闪变"),
+
+    //DataV
+    FreqDev("freq_dev","频率偏差"),
+    Freq("freq","频率"),
+    RmsV("rms","相电压有效值"),
+    VPos("v_pos","正序电压"),
+    VNeg("v_neg","负序电压"),
+    VZero("v_zero","零序电压"),
+    VUnbalance("v_unbalance","电压不平衡度"),
+    RmsLvr("rms_lvr","线电压有效值"),
+    VuDev("vu_dev","线电压正偏差"),
+    VlDev("vl_dev","线电压负偏差"),
+    VThd("v_thd","电压总谐波畸变率"),
+    V_Data("v_1","相（线）电压基波有效值"),
+
+    //r_mp_event_detail
+    VoltageDip("Voltage_Dip","相（线）电压基波有效值"),
+    VoltageRise("Voltage_Rise","相（线）电压基波有效值");
+
+    private String code;
+
+    private String desc;
+
+    DataCleanEnum(String code, String desc) {
+        this.code = code;
+        this.desc = desc;
+    }
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/param/DataCleanParam.java

@@ -0,0 +1,23 @@
+package com.njcn.dataProcess.param;
+
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataCleanParam implements Serializable {
+
+    @ApiModelProperty("系统类型")
+    private String systemType;
+
+    @ApiModelProperty("数据来源")
+    private String dataSource;
+
+    @ApiModelProperty("表名")
+    private String tableName;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/param/LineCountEvaluateParam.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.param;
 import lombok.Data;
 
 import java.io.Serializable;
+import java.time.LocalDateTime;
 import java.util.List;
+import java.util.Map;
 
 /**
  * 监测点有效数值统计数据评估入参
@@ -19,4 +21,15 @@ public class LineCountEvaluateParam extends BaseParam implements Serializable {
      */
     private List<String> lineId;
 
+    /**
+     * 表名
+     */
+    private String tableName;
+
+    /**
+     * 异常数据时间集合
+     * Map<String,List<String>> key:监测点id value:异常时间集合
+     */
+    private Map<String,List<String>> abnormalTime;
+
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataFlicker.java

@@ -31,7 +31,7 @@ public class DataFlicker {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "fluc")
     private Double fluc=0.00;
@@ -56,7 +56,7 @@ public class DataFlicker {
 
         influxDBDataFlicker.setTime(instant);
         influxDBDataFlicker.setLineId(dataFlicker.getLineid());
-        influxDBDataFlicker.setPhaseType(dataFlicker.getPhasicType());
+        influxDBDataFlicker.setPhasicType(dataFlicker.getPhasicType());
         influxDBDataFlicker.setFluc(Objects.isNull(dataFlicker.getFluc())?0.00:dataFlicker.getFluc());
         influxDBDataFlicker.setPlt(Objects.isNull(dataFlicker.getPst())?0.00:dataFlicker.getPst());
         influxDBDataFlicker.setPst(Objects.isNull(dataFlicker.getPlt())?0.00:dataFlicker.getPlt());

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataFluc.java

@@ -31,7 +31,7 @@ public class DataFluc {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "fluc")
     private Double fluc=0.00;
@@ -53,7 +53,7 @@ public class DataFluc {
 
         influxDBDataFluc.setTime(instant);
         influxDBDataFluc.setLineId(dataFluc.getLineid());
-        influxDBDataFluc.setPhaseType(dataFluc.getPhasicType());
+        influxDBDataFluc.setPhasicType(dataFluc.getPhasicType());
         influxDBDataFluc.setFluc(Objects.isNull(dataFluc.getFluc())?0.00:dataFluc.getFluc());
         influxDBDataFluc.setFluccf(Objects.isNull(dataFluc.getFluccf())?0.00:dataFluc.getFluccf());
         influxDBDataFluc.setQualityFlag(dataFluc.getQualityflag()+"");

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmphasicI.java

@@ -35,7 +35,7 @@ public class DataHarmphasicI {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -206,7 +206,7 @@ public class DataHarmphasicI {
 
             influxDBDataHarmPhasicI.setTime(instant);
             influxDBDataHarmPhasicI.setLineId(dataHarmphasicI.getLineid());
-            influxDBDataHarmPhasicI.setPhaseType(dataHarmphasicI.getPhasicType());
+            influxDBDataHarmPhasicI.setPhasicType(dataHarmphasicI.getPhasicType());
             influxDBDataHarmPhasicI.setQualityFlag(dataHarmphasicI.getQualityflag()+"");
             influxDBDataHarmPhasicI.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmphasicV.java

@@ -36,7 +36,7 @@ public class DataHarmphasicV {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -206,7 +206,7 @@ public class DataHarmphasicV {
 
             InfluxDBDataHarmphasicV.setTime(instant);
             InfluxDBDataHarmphasicV.setLineId(dataHarmphasicV.getLineid());
-            InfluxDBDataHarmphasicV.setPhaseType(dataHarmphasicV.getPhasicType());
+            InfluxDBDataHarmphasicV.setPhasicType(dataHarmphasicV.getPhasicType());
             InfluxDBDataHarmphasicV.setQualityFlag(dataHarmphasicV.getQualityflag()+"");
             InfluxDBDataHarmphasicV.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmpowerP.java

@@ -36,7 +36,7 @@ public class DataHarmpowerP {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -215,7 +215,7 @@ public class DataHarmpowerP {
 
             influxDBDataHarmpowerP.setTime(instant);
             influxDBDataHarmpowerP.setLineId(dataHarmpowerP.getLineid());
-            influxDBDataHarmpowerP.setPhaseType(dataHarmpowerP.getPhasicType());
+            influxDBDataHarmpowerP.setPhasicType(dataHarmpowerP.getPhasicType());
             influxDBDataHarmpowerP.setQualityFlag(dataHarmpowerP.getQualityflag()+"");
             influxDBDataHarmpowerP.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmpowerQ.java

@@ -36,7 +36,7 @@ public class DataHarmpowerQ {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -209,7 +209,7 @@ public class DataHarmpowerQ {
 
             influxDBDataHarmpowerQ.setTime(instant);
             influxDBDataHarmpowerQ.setLineId(dataHarmpowerQ.getLineid());
-            influxDBDataHarmpowerQ.setPhaseType(dataHarmpowerQ.getPhasicType());
+            influxDBDataHarmpowerQ.setPhasicType(dataHarmpowerQ.getPhasicType());
             influxDBDataHarmpowerQ.setQualityFlag(dataHarmpowerQ.getQualityflag()+"");
             influxDBDataHarmpowerQ.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmpowerS.java

@@ -36,7 +36,7 @@ public class DataHarmpowerS {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -209,7 +209,7 @@ public class DataHarmpowerS {
 
             influxDBDataHarmpowerS.setTime(instant);
             influxDBDataHarmpowerS.setLineId(dataHarmpowerS.getLineid());
-            influxDBDataHarmpowerS.setPhaseType(dataHarmpowerS.getPhasicType());
+            influxDBDataHarmpowerS.setPhasicType(dataHarmpowerS.getPhasicType());
             influxDBDataHarmpowerS.setQualityFlag(dataHarmpowerS.getQualityflag()+"");
             influxDBDataHarmpowerS.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmrateI.java

@@ -35,7 +35,7 @@ public class DataHarmrateI {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -205,7 +205,7 @@ public class DataHarmrateI {
 
             influxDBDataHarmRateI.setTime(instant);
             influxDBDataHarmRateI.setLineId(dataHarmrateI.getLineid());
-            influxDBDataHarmRateI.setPhaseType(dataHarmrateI.getPhasicType());
+            influxDBDataHarmRateI.setPhasicType(dataHarmrateI.getPhasicType());
             influxDBDataHarmRateI.setQualityFlag(dataHarmrateI.getQualityflag()+"");
             influxDBDataHarmRateI.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataHarmrateV.java

@@ -35,7 +35,7 @@ public class DataHarmrateV {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -205,7 +205,7 @@ public class DataHarmrateV {
 
             influxDBDataHarmRateV.setTime(instant);
             influxDBDataHarmRateV.setLineId(dataHarmrateV.getLineid());
-            influxDBDataHarmRateV.setPhaseType(dataHarmrateV.getPhasicType());
+            influxDBDataHarmRateV.setPhasicType(dataHarmrateV.getPhasicType());
             influxDBDataHarmRateV.setQualityFlag(dataHarmrateV.getQualityflag()+"");
             influxDBDataHarmRateV.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataI.java

@@ -36,7 +36,7 @@ public class DataI {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -224,7 +224,7 @@ public class DataI {
 
             influxDBDataI.setTime(instant);
             influxDBDataI.setLineId(dataI.getLineid());
-            influxDBDataI.setPhaseType(dataI.getPhasicType());
+            influxDBDataI.setPhasicType(dataI.getPhasicType());
             influxDBDataI.setQualityFlag(dataI.getQualityflag()+"");
             influxDBDataI.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataInharmI.java

@@ -36,7 +36,7 @@ public class DataInharmI {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -207,7 +207,7 @@ public class DataInharmI {
 
             influxDBDataInHarmI.setTime(instant);
             influxDBDataInHarmI.setLineId(dataInharmI.getLineid());
-            influxDBDataInHarmI.setPhaseType(dataInharmI.getPhasicType());
+            influxDBDataInHarmI.setPhasicType(dataInharmI.getPhasicType());
             influxDBDataInHarmI.setQualityFlag(dataInharmI.getQualityflag()+"");
             influxDBDataInHarmI.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataInharmV.java

@@ -36,7 +36,7 @@ public class DataInharmV {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -206,7 +206,7 @@ public class DataInharmV {
 
             influxDBDataInHarmV.setTime(instant);
             influxDBDataInHarmV.setLineId(dataInharmV.getLineid());
-            influxDBDataInHarmV.setPhaseType(dataInharmV.getPhasicType());
+            influxDBDataInHarmV.setPhasicType(dataInharmV.getPhasicType());
             influxDBDataInHarmV.setQualityFlag(dataInharmV.getQualityflag()+"");
             influxDBDataInHarmV.setValueType(valueType);
             if (valueType.equals("AVG")) {

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/po/influx/DataPlt.java

@@ -32,7 +32,7 @@ public class DataPlt {
     private String lineId;
 
     @Column(name = "phasic_type",tag = true)
-    private String phaseType;
+    private String phasicType;
 
     @Column(name = "quality_flag",tag = true)
     private String qualityFlag;
@@ -50,7 +50,7 @@ public class DataPlt {
 
         influxDBDataPlt.setTime(instant);
         influxDBDataPlt.setLineId(dataPlt.getLineid());
-        influxDBDataPlt.setPhaseType(dataPlt.getPhasicType());
+        influxDBDataPlt.setPhasicType(dataPlt.getPhasicType());
         influxDBDataPlt.setPlt(Objects.isNull(dataPlt.getPlt())?0.00:dataPlt.getPlt());
         influxDBDataPlt.setQualityFlag(dataPlt.getQualityflag()+"");
 

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/CommonMinuteDto.java

@@ -20,6 +20,9 @@ public class CommonMinuteDto implements Serializable {
     @ApiModelProperty("监测点Id")
     private String lineId;
 
+    @ApiModelProperty("数据质量 0:正常 1:异常")
+    private String qualityFlag;
+
     private List<PhasicType> phasicTypeList;
 
     @Data

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/DataFlickerDto.java

@@ -0,0 +1,45 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataFlickerDto implements Serializable {
+
+    @JsonFormat(pattern = "yyyy-MM-dd")
+    private String time;
+
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private String minTime;
+
+    @ApiModelProperty("监测点Id")
+    private String lineId;
+
+    @ApiModelProperty("相别,'A'表示A相，'B'表示B相,'C'表示C相,'T'表示总, 'M'表示无相别")
+    private String phasicType;
+
+    @ApiModelProperty("数据类型 最大值：max、最小值：min、平均值：avg、95值：cp95")
+    private String valueType;
+
+    @ApiModelProperty("数据质量标志（0-表示是正常数据、1-表示是错误数据、2-表示是有事件的数据）数据库默认是0，污染数据不参与报表统计")
+    private String qualityFlag;
+
+    @ApiModelProperty("数据清洗标识 0:正常 1:异常")
+    private Integer abnormalFlag;
+
+    @ApiModelProperty("电压波动")
+    private Double fluc;
+
+    @ApiModelProperty("短时闪变")
+    private Double pst;
+
+    @ApiModelProperty("长时闪变")
+    private Double plt;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/DataFlucDto.java

@@ -0,0 +1,42 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataFlucDto implements Serializable {
+
+    @JsonFormat(pattern = "yyyy-MM-dd")
+    private String time;
+
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private String minTime;
+
+    @ApiModelProperty("监测点Id")
+    private String lineId;
+
+    @ApiModelProperty("相别,'A'表示A相，'B'表示B相,'C'表示C相,'T'表示总, 'M'表示无相别")
+    private String phasicType;
+
+    @ApiModelProperty("数据类型 最大值：max、最小值：min、平均值：avg、95值：cp95")
+    private String valueType;
+
+    @ApiModelProperty("数据质量标志（0-表示是正常数据、1-表示是错误数据、2-表示是有事件的数据）数据库默认是0，污染数据不参与报表统计")
+    private String qualityFlag;
+
+    @ApiModelProperty("数据清洗标识 0:正常 1:异常")
+    private Integer abnormalFlag;
+
+    @ApiModelProperty("电压波动")
+    private Double fluc;
+
+    @ApiModelProperty("电压波动频度")
+    private Double fluccf;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/DataHarmDto.java

@@ -0,0 +1,145 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataHarmDto implements Serializable {
+
+    @JsonFormat(pattern = "yyyy-MM-dd")
+    private String time;
+
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private String minTime;
+
+    @ApiModelProperty("监测点Id")
+    private String lineId;
+
+    @ApiModelProperty("相别,'A'表示A相，'B'表示B相,'C'表示C相,'T'表示总, 'M'表示无相别")
+    private String phasicType;
+
+    @ApiModelProperty("数据类型 最大值：max、最小值：min、平均值：avg、95值：cp95")
+    private String valueType;
+
+    @ApiModelProperty("数据质量标志（0-表示是正常数据、1-表示是错误数据、2-表示是有事件的数据）数据库默认是0，污染数据不参与报表统计")
+    private String qualityFlag;
+
+    @ApiModelProperty("数据清洗标识 0:正常 1:异常")
+    private Integer abnormalFlag;
+
+    @ApiModelProperty("0.5次间谐波电压含有率")
+    private Double v1;
+
+    @ApiModelProperty("1.5次间谐波电压含有率(2次谐波电压含有率)")
+    private Double v2;
+
+    @ApiModelProperty("2.5次间谐波电压含有率(3次谐波电压含有率)")
+    private Double v3;
+
+    @ApiModelProperty("3.5次间谐波电压含有率(4次谐波电压含有率)")
+    private Double v4;
+
+    @ApiModelProperty("4.5次间谐波电压含有率(5次谐波电压含有率)")
+    private Double v5;
+
+    @ApiModelProperty("5.5次间谐波电压含有率(6次谐波电压含有率)")
+    private Double v6;
+
+    @ApiModelProperty("6.5次间谐波电压含有率(7次谐波电压含有率)")
+    private Double v7;
+
+    @ApiModelProperty("7.5次间谐波电压含有率(8次谐波电压含有率)")
+    private Double v8;
+
+    private Double v9;
+
+    private Double v10;
+
+    private Double v11;
+
+    private Double v12;
+
+    private Double v13;
+
+    private Double v14;
+
+    private Double v15;
+
+    private Double v16;
+
+    private Double v17;
+
+    private Double v18;
+
+    private Double v19;
+
+    private Double v20;
+
+    private Double v21;
+
+    private Double v22;
+
+    private Double v23;
+
+    private Double v24;
+
+    private Double v25;
+
+    private Double v26;
+
+    private Double v27;
+
+    private Double v28;
+
+    private Double v29;
+
+    private Double v30;
+
+    private Double v31;
+
+    private Double v32;
+
+    private Double v33;
+
+    private Double v34;
+
+    private Double v35;
+
+    private Double v36;
+
+    private Double v37;
+
+    private Double v38;
+
+    private Double v39;
+
+    private Double v40;
+
+    private Double v41;
+
+    private Double v42;
+
+    private Double v43;
+
+    private Double v44;
+
+    private Double v45;
+
+    private Double v46;
+
+    private Double v47;
+
+    private Double v48;
+
+    private Double v49;
+
+    @ApiModelProperty("49.5次间谐波电压含有率(50次谐波电压含有率)")
+    private Double v50;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/DataIDto.java

@@ -0,0 +1,163 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataIDto implements Serializable {
+
+    @JsonFormat(pattern = "yyyy-MM-dd")
+    private String time;
+
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private String minTime;
+
+    @ApiModelProperty("监测点Id")
+    private String lineId;
+
+    @ApiModelProperty("相别,'A'表示A相，'B'表示B相,'C'表示C相,'T'表示总, 'M'表示无相别")
+    private String phasicType;
+
+    @ApiModelProperty("数据类型 最大值：max、最小值：min、平均值：avg、95值：cp95")
+    private String valueType;
+
+    @ApiModelProperty("数据质量标志（0-表示是正常数据、1-表示是错误数据、2-表示是有事件的数据）数据库默认是0，污染数据不参与报表统计")
+    private String qualityFlag;
+
+    @ApiModelProperty("数据清洗标识 0:正常 1:异常")
+    private Integer abnormalFlag;
+
+    @ApiModelProperty("负序电流")
+    private Double iNeg;
+
+    @ApiModelProperty("正序电流")
+    private Double iPos;
+
+    @ApiModelProperty("电流总谐波畸变率")
+    private Double iThd;
+
+    @ApiModelProperty("三相电流不平衡度")
+    private Double iUnbalance;
+
+    @ApiModelProperty("零序电流")
+    private Double iZero;
+
+    @ApiModelProperty("电流有效值")
+    private Double rms;
+
+    @ApiModelProperty("基波电流幅值")
+    private Double i1;
+
+    @ApiModelProperty("2次谐波电流幅值")
+    private Double i2;
+
+    @ApiModelProperty("3次谐波电流幅值")
+    private Double i3;
+
+    @ApiModelProperty("4次谐波电流幅值")
+    private Double i4;
+
+    @ApiModelProperty("5次谐波电流幅值")
+    private Double i5;
+
+    @ApiModelProperty("6次谐波电流幅值")
+    private Double i6;
+
+    @ApiModelProperty("7次谐波电流幅值")
+    private Double i7;
+
+    @ApiModelProperty("8次谐波电流幅值")
+    private Double i8;
+
+    private Double i9;
+
+    private Double i10;
+
+    private Double i11;
+
+    private Double i12;
+
+    private Double i13;
+
+    private Double i14;
+
+    private Double i15;
+
+    private Double i16;
+
+    private Double i17;
+
+    private Double i18;
+
+    private Double i19;
+
+    private Double i20;
+
+    private Double i21;
+
+    private Double i22;
+
+    private Double i23;
+
+    private Double i24;
+
+    private Double i25;
+
+    private Double i26;
+
+    private Double i27;
+
+    private Double i28;
+
+    private Double i29;
+
+    private Double i30;
+
+    private Double i31;
+
+    private Double i32;
+
+    private Double i33;
+
+    private Double i34;
+
+    private Double i35;
+
+    private Double i36;
+
+    private Double i37;
+
+    private Double i38;
+
+    private Double i39;
+
+    private Double i40;
+
+    private Double i41;
+
+    private Double i42;
+
+    private Double i43;
+
+    private Double i44;
+
+    private Double i45;
+
+    private Double i46;
+
+    private Double i47;
+
+    private Double i48;
+
+    private Double i49;
+
+    @ApiModelProperty("50次谐波电流幅值")
+    private Double i50;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/DataPltDto.java

@@ -0,0 +1,39 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataPltDto implements Serializable {
+
+    @JsonFormat(pattern = "yyyy-MM-dd")
+    private String time;
+
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private String minTime;
+
+    @ApiModelProperty("监测点Id")
+    private String lineId;
+
+    @ApiModelProperty("相别,'A'表示A相，'B'表示B相,'C'表示C相,'T'表示总, 'M'表示无相别")
+    private String phasicType;
+
+    @ApiModelProperty("数据类型 最大值：max、最小值：min、平均值：avg、95值：cp95")
+    private String valueType;
+
+    @ApiModelProperty("数据质量标志（0-表示是正常数据、1-表示是错误数据、2-表示是有事件的数据）数据库默认是0，污染数据不参与报表统计")
+    private String qualityFlag;
+
+    @ApiModelProperty("数据清洗标识 0:正常 1:异常")
+    private Integer abnormalFlag;
+
+    @ApiModelProperty("长时闪变值")
+    private Double plt;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/DataPowerPDto.java

@@ -0,0 +1,154 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class DataPowerPDto implements Serializable {
+
+    @JsonFormat(pattern = "yyyy-MM-dd")
+    private String time;
+
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private String minTime;
+
+    @ApiModelProperty("监测点Id")
+    private String lineId;
+
+    @ApiModelProperty("相别,'A'表示A相，'B'表示B相,'C'表示C相,'T'表示总, 'M'表示无相别")
+    private String phasicType;
+
+    @ApiModelProperty("数据类型 最大值：max、最小值：min、平均值：avg、95值：cp95")
+    private String valueType;
+
+    @ApiModelProperty("数据质量标志（0-表示是正常数据、1-表示是错误数据、2-表示是有事件的数据）数据库默认是0，污染数据不参与报表统计")
+    private String qualityFlag;
+
+    @ApiModelProperty("数据清洗标识 0:正常 1:异常")
+    private Integer abnormalFlag;
+
+    @ApiModelProperty("位移功率因数")
+    private Double df;
+
+    @ApiModelProperty("视在功率因素")
+    private Double pf;
+
+    @ApiModelProperty("总功功率")
+    private Double p;
+
+    @ApiModelProperty("基波有功功率")
+    private Double p1;
+
+    @ApiModelProperty("2次谐波有功功率")
+    private Double p2;
+
+    @ApiModelProperty("3次谐波有功功率")
+    private Double p3;
+
+    @ApiModelProperty("4次谐波有功功率")
+    private Double p4;
+
+    @ApiModelProperty("5次谐波有功功率")
+    private Double p5;
+
+    @ApiModelProperty("6次谐波有功功率")
+    private Double p6;
+
+    @ApiModelProperty("7次谐波有功功率")
+    private Double p7;
+
+    @ApiModelProperty("8次谐波有功功率")
+    private Double p8;
+
+    private Double p9;
+
+    private Double p10;
+
+    private Double p11;
+
+    private Double p12;
+
+    private Double p13;
+
+    private Double p14;
+
+    private Double p15;
+
+    private Double p16;
+
+    private Double p17;
+
+    private Double p18;
+
+    private Double p19;
+
+    private Double p20;
+
+    private Double p21;
+
+    private Double p22;
+
+    private Double p23;
+
+    private Double p24;
+
+    private Double p25;
+
+    private Double p26;
+
+    private Double p27;
+
+    private Double p28;
+
+    private Double p29;
+
+    private Double p30;
+
+    private Double p31;
+
+    private Double p32;
+
+    private Double p33;
+
+    private Double p34;
+
+    private Double p35;
+
+    private Double p36;
+
+    private Double p37;
+
+    private Double p38;
+
+    private Double p39;
+
+    private Double p40;
+
+    private Double p41;
+
+    private Double p42;
+
+    private Double p43;
+
+    private Double p44;
+
+    private Double p45;
+
+    private Double p46;
+
+    private Double p47;
+
+    private Double p48;
+
+    private Double p49;
+
+    @ApiModelProperty("50次谐波有功功率")
+    private Double p50;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/PqReasonableRangeDto.java

@@ -0,0 +1,100 @@
+package com.njcn.dataProcess.pojo.dto;
+
+import lombok.Data;
+
+import java.io.Serializable;
+
+/**
+ * @author xy
+ */
+@Data
+public class PqReasonableRangeDto implements Serializable {
+
+    private static final long serialVersionUID = 1L;
+
+    /**
+     * 主键ID
+     */
+    private String id;
+
+    /**
+     * 指标code
+     */
+    private String indexCode;
+
+    /**
+     * 指标名称
+     */
+    private String indexName;
+
+    /**
+     * 指标开始
+     */
+    private Integer harmStart;
+
+    /**
+     * 指标结束
+     */
+    private Integer harmEnd;
+
+    /**
+     * 指标所属项别
+     */
+    private String phaseType;
+
+    /**
+     * 指标所属influxdb表的实体类
+     */
+    private String influxdbTableName;
+
+    /**
+     * 指标所属类的属性
+     */
+    private String influxdbColumnName;
+
+    /**
+     * 指标下限
+     */
+    private Double minValue;
+
+    /**
+     * 指标上限
+     */
+    private Double maxValue;
+
+    /**
+     * 电压等级是否参与计算(0:不参与1:参与)
+     */
+    private Integer isVoltage;
+
+    /**
+     * Ct变比是否参与计算
+     */
+    private Integer ctAttendFlag;
+
+    /**
+     * 指标数据源（influxdb，oralce，mysql）
+     */
+    private String dataSource;
+
+    /**
+     * 无具体范围，判断的条件描述
+     */
+    private String otherAlgorithm;
+
+    /**
+     * 备注
+     */
+    private String remark;
+
+    /**
+     * 所属系统（pqs，govern）目前就这个两个系统
+     */
+    private String belongingSystem;
+
+    /**
+     * 状态(0:删除 1:正常)
+     */
+    private Integer state;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/po/PqDataVerify.java

@@ -0,0 +1,96 @@
+package com.njcn.dataProcess.pojo.po;
+
+import com.baomidou.mybatisplus.annotation.TableField;
+import com.baomidou.mybatisplus.annotation.TableName;
+import com.github.jeffreyning.mybatisplus.anno.MppMultiId;
+import lombok.Getter;
+import lombok.Setter;
+
+import java.io.Serializable;
+import java.math.BigDecimal;
+import java.time.LocalDateTime;
+
+/**
+ * <p>
+ * 
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-17
+ */
+@Getter
+@Setter
+@TableName("pq_data_verify")
+public class PqDataVerify implements Serializable {
+
+    private static final long serialVersionUID = 1L;
+
+    /**
+     * 监测点id
+     */
+    @MppMultiId
+    @TableField(value = "line_id")
+    private String lineId;
+
+    /**
+     * 异常数据时间
+     */
+    @MppMultiId
+    @TableField(value = "time")
+    private LocalDateTime time;
+
+    /**
+     * 数据类型(最大值：max、最小值：min、平均值：avg、95值：cp95)
+     */
+    @MppMultiId
+    @TableField(value = "value_type")
+    private String valueType;
+
+    /**
+     * 相别："A" "B" "C" "ABC" "T"
+     */
+    @MppMultiId
+    @TableField(value = "phasic_type")
+    private String phasicType;
+
+    /**
+     * 指标code
+     */
+    @MppMultiId
+    @TableField(value = "index_code")
+    private String indexCode;
+
+    /**
+     * 指标名称
+     */
+    @MppMultiId
+    @TableField(value = "index_name")
+    private String indexName;
+
+    /**
+     * 指标表名
+     */
+    @MppMultiId
+    @TableField(value = "index_table")
+    private String indexTable;
+
+    /**
+     * 异常值
+     */
+    @TableField(value = "abnormal_value")
+    private Double abnormalValue;
+
+    /**
+     * 指标上限
+     */
+    @TableField(value = "min_value")
+    private Double minValue;
+
+    /**
+     * 指标下限
+     */
+    @TableField(value = "max_value")
+    private Double maxValue;
+
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/po/PqReasonableRange.java

@@ -0,0 +1,110 @@
+package com.njcn.dataProcess.pojo.po;
+
+import com.baomidou.mybatisplus.annotation.TableName;
+import com.njcn.db.bo.BaseEntity;
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+
+import java.io.Serializable;
+
+/**
+ * <p>
+ * 
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-13
+ */
+@Data
+@EqualsAndHashCode(callSuper = true)
+@TableName("pq_reasonable_range")
+public class PqReasonableRange extends BaseEntity implements Serializable {
+
+    private static final long serialVersionUID = 1L;
+
+    /**
+     * 主键ID
+     */
+    private String id;
+
+    /**
+     * 指标code
+     */
+    private String indexCode;
+
+    /**
+     * 指标名称
+     */
+    private String indexName;
+
+    /**
+     * 指标开始
+     */
+    private Integer harmStart;
+
+    /**
+     * 指标结束
+     */
+    private Integer harmEnd;
+
+    /**
+     * 指标所属项别
+     */
+    private String phaseType;
+
+    /**
+     * 指标所属influxdb表的实体类
+     */
+    private String influxdbTableName;
+
+    /**
+     * 指标所属类的属性
+     */
+    private String influxdbColumnName;
+
+    /**
+     * 指标下限
+     */
+    private Double minValue;
+
+    /**
+     * 指标上限
+     */
+    private Double maxValue;
+
+    /**
+     * 电压等级是否参与计算(0:不参与1:参与)
+     */
+    private Integer isVoltage;
+
+    /**
+     * Ct变比是否参与计算
+     */
+    private Integer ctAttendFlag;
+
+    /**
+     * 指标数据源（influxdb，oralce，mysql）
+     */
+    private String dataSource;
+
+    /**
+     * 无具体范围，判断的条件描述
+     */
+    private String otherAlgorithm;
+
+    /**
+     * 备注
+     */
+    private String remark;
+
+    /**
+     * 所属系统（pqs，govern）目前就这个两个系统
+     */
+    private String belongingSystem;
+
+    /**
+     * 状态(0:删除 1:正常)
+     */
+    private Integer state;
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/po/RStatDataVD.java

@@ -1,7 +1,6 @@
 package com.njcn.dataProcess.pojo.po;
 
-import com.baomidou.mybatisplus.annotation.TableField;
-import com.baomidou.mybatisplus.annotation.TableName;
+import com.baomidou.mybatisplus.annotation.*;
 import com.github.jeffreyning.mybatisplus.anno.MppMultiId;
 import lombok.Data;
 
@@ -37,187 +36,187 @@ public class RStatDataVD implements Serializable {
     @TableField(value = "quality_flag")
     private Integer qualityFlag;
 
-    @TableField(value = "freq")
+    @TableField(value = "freq",updateStrategy = FieldStrategy.IGNORED)
     private Double freq;
 
-    @TableField(value = "freq_dev")
+    @TableField(value = "freq_dev",updateStrategy = FieldStrategy.IGNORED)
     private Double freqDev;
 
-    @TableField(value = "rms")
+    @TableField(value = "rms",updateStrategy = FieldStrategy.IGNORED)
     private Double rms;
 
-    @TableField(value = "rms_lvr")
+    @TableField(value = "rms_lvr",updateStrategy = FieldStrategy.IGNORED)
     private Double rmsLvr;
 
-    @TableField(value = "v_neg")
+    @TableField(value = "v_neg",updateStrategy = FieldStrategy.IGNORED)
     private Double vNeg;
 
-    @TableField(value = "v_pos")
+    @TableField(value = "v_pos",updateStrategy = FieldStrategy.IGNORED)
     private Double vPos;
 
-    @TableField(value = "v_thd")
+    @TableField(value = "v_thd",updateStrategy = FieldStrategy.IGNORED)
     private Double vThd;
 
-    @TableField(value = "v_unbalance")
+    @TableField(value = "v_unbalance",updateStrategy = FieldStrategy.IGNORED)
     private Double vUnbalance;
 
-    @TableField(value = "v_zero")
+    @TableField(value = "v_zero",updateStrategy = FieldStrategy.IGNORED)
     private Double vZero;
 
-    @TableField(value = "vl_dev")
+    @TableField(value = "vl_dev",updateStrategy = FieldStrategy.IGNORED)
     private Double vlDev;
 
-    @TableField(value = "vu_dev")
+    @TableField(value = "vu_dev",updateStrategy = FieldStrategy.IGNORED)
     private Double vuDev;
 
-    @TableField(value = "v_1")
+    @TableField(value = "v_1",updateStrategy = FieldStrategy.IGNORED)
     private Double v1;
 
-    @TableField(value = "v_2")
+    @TableField(value = "v_2",updateStrategy = FieldStrategy.IGNORED)
     private Double v2;
 
-    @TableField(value = "v_3")
+    @TableField(value = "v_3",updateStrategy = FieldStrategy.IGNORED)
     private Double v3;
 
-    @TableField(value = "v_4")
+    @TableField(value = "v_4",updateStrategy = FieldStrategy.IGNORED)
     private Double v4;
 
-    @TableField(value = "v_5")
+    @TableField(value = "v_5",updateStrategy = FieldStrategy.IGNORED)
     private Double v5;
 
-    @TableField(value = "v_6")
+    @TableField(value = "v_6",updateStrategy = FieldStrategy.IGNORED)
     private Double v6;
 
-    @TableField(value = "v_7")
+    @TableField(value = "v_7",updateStrategy = FieldStrategy.IGNORED)
     private Double v7;
 
-    @TableField(value = "v_8")
+    @TableField(value = "v_8",updateStrategy = FieldStrategy.IGNORED)
     private Double v8;
 
-    @TableField(value = "v_9")
+    @TableField(value = "v_9",updateStrategy = FieldStrategy.IGNORED)
     private Double v9;
 
-    @TableField(value = "v_10")
+    @TableField(value = "v_10",updateStrategy = FieldStrategy.IGNORED)
     private Double v10;
 
-    @TableField(value = "v_11")
+    @TableField(value = "v_11",updateStrategy = FieldStrategy.IGNORED)
     private Double v11;
 
-    @TableField(value = "v_12")
+    @TableField(value = "v_12",updateStrategy = FieldStrategy.IGNORED)
     private Double v12;
 
-    @TableField(value = "v_13")
+    @TableField(value = "v_13",updateStrategy = FieldStrategy.IGNORED)
     private Double v13;
 
-    @TableField(value = "v_14")
+    @TableField(value = "v_14",updateStrategy = FieldStrategy.IGNORED)
     private Double v14;
 
-    @TableField(value = "v_15")
+    @TableField(value = "v_15",updateStrategy = FieldStrategy.IGNORED)
     private Double v15;
 
-    @TableField(value = "v_16")
+    @TableField(value = "v_16",updateStrategy = FieldStrategy.IGNORED)
     private Double v16;
 
-    @TableField(value = "v_17")
+    @TableField(value = "v_17",updateStrategy = FieldStrategy.IGNORED)
     private Double v17;
 
-    @TableField(value = "v_18")
+    @TableField(value = "v_18",updateStrategy = FieldStrategy.IGNORED)
     private Double v18;
 
-    @TableField(value = "v_19")
+    @TableField(value = "v_19",updateStrategy = FieldStrategy.IGNORED)
     private Double v19;
 
-    @TableField(value = "v_20")
+    @TableField(value = "v_20",updateStrategy = FieldStrategy.IGNORED)
     private Double v20;
 
-    @TableField(value = "v_21")
+    @TableField(value = "v_21",updateStrategy = FieldStrategy.IGNORED)
     private Double v21;
 
-    @TableField(value = "v_22")
+    @TableField(value = "v_22",updateStrategy = FieldStrategy.IGNORED)
     private Double v22;
 
-    @TableField(value = "v_23")
+    @TableField(value = "v_23",updateStrategy = FieldStrategy.IGNORED)
     private Double v23;
 
-    @TableField(value = "v_24")
+    @TableField(value = "v_24",updateStrategy = FieldStrategy.IGNORED)
     private Double v24;
 
-    @TableField(value = "v_25")
+    @TableField(value = "v_25",updateStrategy = FieldStrategy.IGNORED)
     private Double v25;
 
-    @TableField(value = "v_26")
+    @TableField(value = "v_26",updateStrategy = FieldStrategy.IGNORED)
     private Double v26;
 
-    @TableField(value = "v_27")
+    @TableField(value = "v_27",updateStrategy = FieldStrategy.IGNORED)
     private Double v27;
 
-    @TableField(value = "v_28")
+    @TableField(value = "v_28",updateStrategy = FieldStrategy.IGNORED)
     private Double v28;
 
-    @TableField(value = "v_29")
+    @TableField(value = "v_29",updateStrategy = FieldStrategy.IGNORED)
     private Double v29;
 
-    @TableField(value = "v_30")
+    @TableField(value = "v_30",updateStrategy = FieldStrategy.IGNORED)
     private Double v30;
 
-    @TableField(value = "v_31")
+    @TableField(value = "v_31",updateStrategy = FieldStrategy.IGNORED)
     private Double v31;
 
-    @TableField(value = "v_32")
+    @TableField(value = "v_32",updateStrategy = FieldStrategy.IGNORED)
     private Double v32;
 
-    @TableField(value = "v_33")
+    @TableField(value = "v_33",updateStrategy = FieldStrategy.IGNORED)
     private Double v33;
 
-    @TableField(value = "v_34")
+    @TableField(value = "v_34",updateStrategy = FieldStrategy.IGNORED)
     private Double v34;
 
-    @TableField(value = "v_35")
+    @TableField(value = "v_35",updateStrategy = FieldStrategy.IGNORED)
     private Double v35;
 
-    @TableField(value = "v_36")
+    @TableField(value = "v_36",updateStrategy = FieldStrategy.IGNORED)
     private Double v36;
 
-    @TableField(value = "v_37")
+    @TableField(value = "v_37",updateStrategy = FieldStrategy.IGNORED)
     private Double v37;
 
-    @TableField(value = "v_38")
+    @TableField(value = "v_38",updateStrategy = FieldStrategy.IGNORED)
     private Double v38;
 
-    @TableField(value = "v_39")
+    @TableField(value = "v_39",updateStrategy = FieldStrategy.IGNORED)
     private Double v39;
 
-    @TableField(value = "v_40")
+    @TableField(value = "v_40",updateStrategy = FieldStrategy.IGNORED)
     private Double v40;
 
-    @TableField(value = "v_41")
+    @TableField(value = "v_41",updateStrategy = FieldStrategy.IGNORED)
     private Double v41;
 
-    @TableField(value = "v_42")
+    @TableField(value = "v_42",updateStrategy = FieldStrategy.IGNORED)
     private Double v42;
 
-    @TableField(value = "v_43")
+    @TableField(value = "v_43",updateStrategy = FieldStrategy.IGNORED)
     private Double v43;
 
-    @TableField(value = "v_44")
+    @TableField(value = "v_44",updateStrategy = FieldStrategy.IGNORED)
     private Double v44;
 
-    @TableField(value = "v_45")
+    @TableField(value = "v_45",updateStrategy = FieldStrategy.IGNORED)
     private Double v45;
 
-    @TableField(value = "v_46")
+    @TableField(value = "v_46",updateStrategy = FieldStrategy.IGNORED)
     private Double v46;
 
-    @TableField(value = "v_47")
+    @TableField(value = "v_47",updateStrategy = FieldStrategy.IGNORED)
     private Double v47;
 
-    @TableField(value = "v_48")
+    @TableField(value = "v_48",updateStrategy = FieldStrategy.IGNORED)
     private Double v48;
 
-    @TableField(value = "v_49")
+    @TableField(value = "v_49",updateStrategy = FieldStrategy.IGNORED)
     private Double v49;
 
-    @TableField(value = "v_50")
+    @TableField(value = "v_50",updateStrategy = FieldStrategy.IGNORED)
     private Double v50;
 
 }

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/util/DataCommonUtils.java

@@ -0,0 +1,20 @@
+package com.njcn.dataProcess.util;
+
+/**
+ * @author xy
+ * @description 公共方法
+ */
+
+public class DataCommonUtils {
+
+    /**
+     * 传入字典类型的电压等级，获取可以计算的数据
+     * 例如 35kV->32.0
+     *     0.38kV->0.38
+     */
+    public static Double getVoltageData(String lineVoltage) {
+        String numberStr = lineVoltage.replace("kV", "");
+        return Double.parseDouble(numberStr);
+    }
+
+}

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/util/TimeUtils.java

@@ -27,6 +27,24 @@ public class TimeUtils {
         return dateTime.toLocalDate();
     }
 
+    /**
+     * String类型的yyyy-MM-dd HH:mm:ss转成LocalDataTime yyyy-MM-dd HH:mm:ss
+     * @param time
+     * @return LocalDataTime
+     */
+    public static LocalDateTime StringToLocalDateTime(String time) {
+        return LocalDateTime.parse(time, DATE_TIME_FORMATTER);
+    }
+
+    /**
+     * LocalDataTime类型的yyyy-MM-dd HH:mm:ss转成String yyyy-MM-dd HH:mm:ss
+     * @param time
+     * @return LocalDataTime
+     */
+    public static String LocalDateTimeToString(LocalDateTime time) {
+        return time.format(DATE_TIME_FORMATTER);
+    }
+
     /**
      * String类型的yyyy-MM-dd转成yyyy-MM-dd
      * @param time

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataFlickerController.java

@@ -6,10 +6,11 @@ import com.njcn.common.pojo.enums.common.LogEnum;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.common.utils.HttpResultUtil;
-
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
 import com.njcn.dataProcess.dto.DataFlickerDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlickerDto;
 import com.njcn.dataProcess.service.IDataFlicker;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -54,7 +55,14 @@ public class DataFlickerController extends BaseController {
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
     }
 
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataFlickerDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataFlickerDto> data = dataFlickerQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 
 

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataFlucController.java

@@ -6,9 +6,12 @@ import com.njcn.common.pojo.enums.common.LogEnum;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.common.utils.HttpResultUtil;
-import com.njcn.dataProcess.dto.DataFlucDTO;
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.dto.DataFlucDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlucDto;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 import com.njcn.dataProcess.service.IDataFluc;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -42,7 +45,6 @@ public class DataFlucController extends BaseController {
     @InsertBean
     private IDataFluc dataFlucInsert;
 
-
     @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.ADD)
     @PostMapping("/batchInsertion")
     @ApiOperation("批量插入")
@@ -53,9 +55,13 @@ public class DataFlucController extends BaseController {
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
     }
 
-
-
-
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataFlucDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataFlucDto> data = dataFlucQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataHarmRateVController.java

@@ -0,0 +1,55 @@
+package com.njcn.dataProcess.controller;
+
+import com.njcn.common.pojo.annotation.OperateInfo;
+import com.njcn.common.pojo.constant.OperateType;
+import com.njcn.common.pojo.enums.common.LogEnum;
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.common.utils.HttpResultUtil;
+import com.njcn.dataProcess.annotation.InsertBean;
+import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+import com.njcn.dataProcess.service.IDataHarmRateV;
+import com.njcn.web.controller.BaseController;
+import io.swagger.annotations.Api;
+import io.swagger.annotations.ApiOperation;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Controller;
+import org.springframework.validation.annotation.Validated;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+import java.util.List;
+
+/**
+ * @author hongawen
+ * @version 1.0
+ * @data 2024/11/6 19:48
+ */
+@Validated
+@Slf4j
+@Controller
+@RestController
+@RequestMapping("/dataHarmRateV")
+@Api(tags = "谐波电压含有率")
+public class DataHarmRateVController extends BaseController {
+
+    @QueryBean
+    private IDataHarmRateV dataHarmRateVQuery;
+
+    @InsertBean
+    private IDataHarmRateV dataHarmRateVInsert;
+
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataHarmDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataHarmDto> data = dataHarmRateVQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
+
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataHarmphasicVController.java

@@ -6,9 +6,11 @@ import com.njcn.common.pojo.enums.common.LogEnum;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.common.utils.HttpResultUtil;
-import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.service.IDataHarmphasicV;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -54,7 +56,14 @@ public class DataHarmphasicVController extends BaseController {
     }
 
 
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataHarmDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataHarmDto> data = dataHarmphasicVQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 
 

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataHarmpowerPController.java

@@ -6,9 +6,11 @@ import com.njcn.common.pojo.enums.common.LogEnum;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.common.utils.HttpResultUtil;
-import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataPowerPDto;
 import com.njcn.dataProcess.service.IDataHarmpowerP;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -53,9 +55,13 @@ public class DataHarmpowerPController extends BaseController {
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
     }
 
-
-
-
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataPowerPDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataPowerPDto> data = dataHarmpowerPQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataIController.java

@@ -6,9 +6,11 @@ import com.njcn.common.pojo.enums.common.LogEnum;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.common.utils.HttpResultUtil;
-import com.njcn.dataProcess.dto.DataIDTO;
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.dto.DataIDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
 import com.njcn.dataProcess.service.IDataI;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -53,9 +55,13 @@ public class DataIController extends BaseController {
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
     }
 
-
-
-
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataIDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataIDto> data = dataIQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataInharmVController.java

@@ -9,6 +9,8 @@ import com.njcn.common.utils.HttpResultUtil;
 import com.njcn.dataProcess.dto.DataInharmVDTO;
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.service.IDataInharmV;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -53,9 +55,14 @@ public class DataInharmVController extends BaseController {
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
     }
 
-
-
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataHarmDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataHarmDto> data = dataInharmVQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataPltController.java

@@ -6,9 +6,11 @@ import com.njcn.common.pojo.enums.common.LogEnum;
 import com.njcn.common.pojo.enums.response.CommonResponseEnum;
 import com.njcn.common.pojo.response.HttpResult;
 import com.njcn.common.utils.HttpResultUtil;
-import com.njcn.dataProcess.dto.DataPltDTO;
 import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.annotation.QueryBean;
+import com.njcn.dataProcess.dto.DataPltDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 import com.njcn.dataProcess.service.IDataPlt;
 import com.njcn.web.controller.BaseController;
 import io.swagger.annotations.Api;
@@ -53,9 +55,14 @@ public class DataPltController extends BaseController {
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
     }
 
-
-
-
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getRawData")
+    @ApiOperation("获取原始数据")
+    public HttpResult<List<DataPltDto>> getRawData(@RequestBody LineCountEvaluateParam lineParam) {
+        String methodDescribe = getMethodDescribe("getRawData");
+        List<DataPltDto> data = dataPltQuery.getRawData(lineParam);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, data, methodDescribe);
+    }
 
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/DataVController.java

@@ -105,9 +105,10 @@ public class DataVController extends BaseController {
     @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.ADD)
     @PostMapping("/addInfluxDbList")
     @ApiOperation("时序数据库插入数据")
+    @Deprecated
     public HttpResult<String> addInfluxDbList(@RequestBody List<DataVDto> dataVList) {
         String methodDescribe = getMethodDescribe("addInfluxDbList");
-        dataVInsert.addInfluxDbList(dataVList);
+        dataVQuery.addInfluxDbList(dataVList);
         return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, "", methodDescribe);
     }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/PqDataVerifyController.java

@@ -0,0 +1,57 @@
+package com.njcn.dataProcess.controller;
+
+
+import com.njcn.common.pojo.annotation.OperateInfo;
+import com.njcn.common.pojo.constant.OperateType;
+import com.njcn.common.pojo.enums.common.LogEnum;
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.common.utils.HttpResultUtil;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+import com.njcn.dataProcess.service.IPqDataVerifyService;
+import com.njcn.web.controller.BaseController;
+import io.swagger.annotations.ApiOperation;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+import javax.annotation.Resource;
+import java.util.List;
+
+/**
+ * <p>
+ *  前端控制器
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-17
+ */
+@RestController
+@RequestMapping("/pqDataVerify")
+public class PqDataVerifyController extends BaseController {
+
+    @Resource
+    private IPqDataVerifyService pqDataVerifyService;
+
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.ADD)
+    @PostMapping("/insertData")
+    @ApiOperation("存储清洗的异常数据")
+    public HttpResult<List<PqDataVerify>> insertData(@RequestBody List<PqDataVerify> list) {
+        String methodDescribe = getMethodDescribe("insertData");
+        pqDataVerifyService.insertData(list);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, null, methodDescribe);
+    }
+
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/queryData")
+    @ApiOperation("查询清洗的异常数据")
+    public HttpResult<List<PqDataVerify>> queryData(@RequestBody LineCountEvaluateParam param) {
+        String methodDescribe = getMethodDescribe("queryData");
+        List<PqDataVerify> list = pqDataVerifyService.queryData(param);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, list, methodDescribe);
+    }
+
+}
+

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/controller/PqReasonableRangeController.java

@@ -0,0 +1,56 @@
+package com.njcn.dataProcess.controller;
+
+
+import com.njcn.common.pojo.annotation.OperateInfo;
+import com.njcn.common.pojo.constant.OperateType;
+import com.njcn.common.pojo.enums.common.LogEnum;
+import com.njcn.common.pojo.enums.response.CommonResponseEnum;
+import com.njcn.common.pojo.response.HttpResult;
+import com.njcn.common.utils.HttpResultUtil;
+import com.njcn.dataProcess.param.DataCleanParam;
+import com.njcn.dataProcess.pojo.dto.PqReasonableRangeDto;
+import com.njcn.dataProcess.service.IPqReasonableRangeService;
+import com.njcn.web.controller.BaseController;
+import io.swagger.annotations.Api;
+import io.swagger.annotations.ApiOperation;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Controller;
+import org.springframework.validation.annotation.Validated;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+import javax.annotation.Resource;
+import java.util.List;
+
+/**
+ * <p>
+ *  前端控制器
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-13
+ */
+@Validated
+@Slf4j
+@Controller
+@RestController
+@RequestMapping("/pqReasonableRange")
+@Api(tags = "数据清洗标准库")
+public class PqReasonableRangeController extends BaseController {
+
+    @Resource
+    private IPqReasonableRangeService pqReasonableRangeService;
+
+    @OperateInfo(info = LogEnum.BUSINESS_COMMON,operateType = OperateType.QUERY)
+    @PostMapping("/getData")
+    @ApiOperation("按条件获取数据合理范围")
+    public HttpResult<List<PqReasonableRangeDto>> getData(@RequestBody DataCleanParam param) {
+        String methodDescribe = getMethodDescribe("getData");
+        List<PqReasonableRangeDto> list = pqReasonableRangeService.getReasonableRangeList(param);
+        return HttpResultUtil.assembleCommonResponseResult(CommonResponseEnum.SUCCESS, list, methodDescribe);
+    }
+
+}
+

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/dao/imapper/DataHarmRateVMapper.java

@@ -0,0 +1,14 @@
+package com.njcn.dataProcess.dao.imapper;
+
+import com.njcn.dataProcess.po.influx.DataHarmrateV;
+import com.njcn.influx.base.InfluxDbBaseMapper;
+
+
+/**
+ * @author xy
+ */
+public interface DataHarmRateVMapper extends InfluxDbBaseMapper<DataHarmrateV> {
+
+
+
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/dao/relation/mapper/PqDataVerifyMapper.java

@@ -0,0 +1,16 @@
+package com.njcn.dataProcess.dao.relation.mapper;
+
+import com.github.jeffreyning.mybatisplus.base.MppBaseMapper;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+
+/**
+ * <p>
+ *  Mapper 接口
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-17
+ */
+public interface PqDataVerifyMapper extends MppBaseMapper<PqDataVerify> {
+
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/dao/relation/mapper/PqReasonableRangeMapper.java

@@ -0,0 +1,18 @@
+package com.njcn.dataProcess.dao.relation.mapper;
+
+import com.baomidou.mybatisplus.core.mapper.BaseMapper;
+import com.njcn.dataProcess.pojo.dto.PqReasonableRangeDto;
+import com.njcn.dataProcess.pojo.po.PqReasonableRange;
+
+import java.util.List;
+
+/**
+ * <p>
+ *  Mapper 接口
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-13
+ */
+public interface PqReasonableRangeMapper extends BaseMapper<PqReasonableRange> {
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataFlicker.java

@@ -1,6 +1,8 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataFlickerDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlickerDto;
 
 import java.util.List;
 
@@ -13,4 +15,11 @@ import java.util.List;
  */
 public interface IDataFlicker {
     void batchInsertion(List<DataFlickerDTO> dataIDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataFlickerDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataFluc.java

@@ -1,6 +1,8 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataFlucDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataFlucDto;
 
 import java.util.List;
 
@@ -13,4 +15,11 @@ import java.util.List;
  */
 public interface IDataFluc {
     void batchInsertion(List<DataFlucDTO> dataIDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataFlucDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataHarmRateV.java

@@ -0,0 +1,19 @@
+package com.njcn.dataProcess.service;
+
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+
+import java.util.List;
+
+/**
+ * @author xy
+ */
+public interface IDataHarmRateV {
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam);
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataHarmphasicV.java

@@ -1,6 +1,8 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 
 import java.util.List;
 
@@ -13,4 +15,11 @@ import java.util.List;
  */
 public interface IDataHarmphasicV {
     void batchInsertion(List<DataHarmphasicVDTO> dataIDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataHarmpowerP.java

@@ -1,6 +1,9 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
+import com.njcn.dataProcess.pojo.dto.DataPowerPDto;
 
 import java.util.List;
 
@@ -13,4 +16,11 @@ import java.util.List;
  */
 public interface IDataHarmpowerP {
     void batchInsertion(List<DataHarmpowerPDTO> dataIDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataPowerPDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataI.java

@@ -1,6 +1,10 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataIDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.po.influx.DataI;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
+import com.njcn.dataProcess.pojo.dto.DataVDto;
 
 import java.util.List;
 
@@ -12,5 +16,13 @@ import java.util.List;
  * @version V1.0.0
  */
 public interface IDataI {
+
     void batchInsertion(List<DataIDTO> dataIDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataIDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataInharmV.java

@@ -1,6 +1,8 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataInharmVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 
 import java.util.List;
 
@@ -14,4 +16,11 @@ import java.util.List;
 public interface IDataInharmV {
 
     void batchInsertion(List<DataInharmVDTO> dataIDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataPlt.java

@@ -1,6 +1,9 @@
 package com.njcn.dataProcess.service;
 
 import com.njcn.dataProcess.dto.DataPltDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 
 import java.util.List;
 
@@ -13,4 +16,11 @@ import java.util.List;
  */
 public interface IDataPlt {
     void batchInsertion(List<DataPltDTO> dataPltDTOList);
+
+    /**
+     * 获取原始数据
+     * @param lineParam
+     * @return
+     */
+    List<DataPltDto> getRawData(LineCountEvaluateParam lineParam);
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IDataV.java

@@ -4,7 +4,6 @@ import com.github.jeffreyning.mybatisplus.service.IMppService;
 import com.njcn.dataProcess.dto.DataVDTO;
 import com.njcn.dataProcess.dto.DataVFiveItemDTO;
 import com.njcn.dataProcess.param.LineCountEvaluateParam;
-import com.njcn.dataProcess.po.influx.DataV;
 import com.njcn.dataProcess.pojo.dto.CommonMinuteDto;
 import com.njcn.dataProcess.pojo.dto.DataVDto;
 import com.njcn.dataProcess.pojo.po.RStatDataVD;

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IPqDataVerifyService.java

@@ -0,0 +1,30 @@
+package com.njcn.dataProcess.service;
+
+import com.github.jeffreyning.mybatisplus.service.IMppService;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+
+import java.util.List;
+
+/**
+ * <p>
+ *  服务类
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-17
+ */
+public interface IPqDataVerifyService extends IMppService<PqDataVerify> {
+
+    /**
+     * 异常数据插入
+     * @param list
+     */
+    void insertData(List<PqDataVerify> list);
+
+    /**
+     * 异常数据查询
+     * @param param
+     */
+    List<PqDataVerify> queryData(LineCountEvaluateParam param);
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/IPqReasonableRangeService.java

@@ -0,0 +1,27 @@
+package com.njcn.dataProcess.service;
+
+import com.baomidou.mybatisplus.extension.service.IService;
+import com.njcn.dataProcess.param.DataCleanParam;
+import com.njcn.dataProcess.pojo.dto.PqReasonableRangeDto;
+import com.njcn.dataProcess.pojo.po.PqReasonableRange;
+
+import java.util.List;
+
+/**
+ * <p>
+ *  服务类
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-13
+ */
+public interface IPqReasonableRangeService extends IService<PqReasonableRange> {
+
+    /**
+     * 根据条件获取稳态指标正常范围数据
+     * @param param
+     * @return
+     */
+    List<PqReasonableRangeDto> getReasonableRangeList(DataCleanParam param);
+
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataFlickerImpl.java

@@ -1,15 +1,23 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
-import com.njcn.dataProcess.dto.DataFlickerDTO;
+import cn.hutool.core.collection.CollectionUtil;
 import com.njcn.dataProcess.dao.imapper.DataFlickerMapper;
+import com.njcn.dataProcess.dto.DataFlickerDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.influx.DataFlicker;
+import com.njcn.dataProcess.pojo.dto.DataFlickerDto;
 import com.njcn.dataProcess.service.IDataFlicker;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -23,6 +31,8 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataFlickerImpl implements IDataFlicker {
 
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
     private final DataFlickerMapper dataFlickerMapper;
 
 
@@ -44,4 +54,69 @@ public class InfluxdbDataFlickerImpl implements IDataFlicker {
 
         }
     }
+
+    @Override
+    public List<DataFlickerDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataFlickerDto> result = new ArrayList<>();
+        List<DataFlicker> list = getMinuteData(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataFlickerDto dto = new DataFlickerDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataFlicker> getMinuteData(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataFlicker> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataFlicker.class);
+        influxQueryWrapper.regular(DataFlicker::getLineId, lineList)
+                .select(DataFlicker::getLineId)
+                .select(DataFlicker::getPhasicType)
+                .select(DataFlicker::getFluc)
+                .select(DataFlicker::getPst)
+                .select(DataFlicker::getPlt)
+                .select(DataFlicker::getQualityFlag)
+                .between(DataFlicker::getTime, startTime, endTime)
+                .eq(DataFlicker::getQualityFlag,"0");
+        List<DataFlicker> list = dataFlickerMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataFlicker>> lineMap = list.stream().collect(Collectors.groupingBy(DataFlicker::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataFlicker> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataFlucImpl.java

@@ -1,15 +1,23 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
-import com.njcn.dataProcess.dto.DataFlucDTO;
+import cn.hutool.core.collection.CollectionUtil;
 import com.njcn.dataProcess.dao.imapper.DataFlucMapper;
+import com.njcn.dataProcess.dto.DataFlucDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.influx.DataFluc;
+import com.njcn.dataProcess.pojo.dto.DataFlucDto;
 import com.njcn.dataProcess.service.IDataFluc;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -23,6 +31,8 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataFlucImpl implements IDataFluc {
 
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
     private final DataFlucMapper dataFlucMapper;
 
 
@@ -44,4 +54,68 @@ public class InfluxdbDataFlucImpl implements IDataFluc {
 
         }
     }
+
+    @Override
+    public List<DataFlucDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataFlucDto> result = new ArrayList<>();
+        List<DataFluc> list = getMinuteData(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataFlucDto dto = new DataFlucDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataFluc> getMinuteData(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataFluc> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataFluc.class);
+        influxQueryWrapper.regular(DataFluc::getLineId, lineList)
+                .select(DataFluc::getLineId)
+                .select(DataFluc::getPhasicType)
+                .select(DataFluc::getFluc)
+                .select(DataFluc::getFluccf)
+                .select(DataFluc::getQualityFlag)
+                .between(DataFluc::getTime, startTime, endTime)
+                .eq(DataFluc::getQualityFlag,"0");
+        List<DataFluc> list = dataFlucMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataFluc>> lineMap = list.stream().collect(Collectors.groupingBy(DataFluc::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataFluc> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataHarmRateVImpl.java

@@ -0,0 +1,98 @@
+package com.njcn.dataProcess.service.impl.influxdb;
+
+import cn.hutool.core.collection.CollectionUtil;
+import com.njcn.common.utils.HarmonicTimesUtil;
+import com.njcn.dataProcess.dao.imapper.DataHarmRateVMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.po.influx.DataHarmrateV;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+import com.njcn.dataProcess.service.IDataHarmRateV;
+import com.njcn.influx.constant.InfluxDbSqlConstant;
+import com.njcn.influx.query.InfluxQueryWrapper;
+import lombok.RequiredArgsConstructor;
+import org.springframework.beans.BeanUtils;
+import org.springframework.stereotype.Service;
+
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+/**
+ * @author xy
+ */
+@Service("InfluxdbDataHarmRateVImpl")
+@RequiredArgsConstructor
+public class InfluxdbDataHarmRateVImpl implements IDataHarmRateV {
+
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
+    private final DataHarmRateVMapper dataHarmRateVMapper;
+
+    @Override
+    public List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataHarmDto> result = new ArrayList<>();
+        List<DataHarmrateV> list = getMinuteDataI(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataHarmDto dto = new DataHarmDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取dataI分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataHarmrateV> getMinuteDataI(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataHarmrateV> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataHarmrateV.class);
+        influxQueryWrapper.samePrefixAndSuffix(InfluxDbSqlConstant.V, "", HarmonicTimesUtil.harmonicTimesList(2, 50, 1));
+        influxQueryWrapper.regular(DataHarmrateV::getLineId, lineList)
+                .select(DataHarmrateV::getLineId)
+                .select(DataHarmrateV::getPhasicType)
+                .select(DataHarmrateV::getValueType)
+                .select(DataHarmrateV::getQualityFlag)
+                .between(DataHarmrateV::getTime, startTime, endTime)
+                .eq(DataHarmrateV::getQualityFlag,"0");
+        List<DataHarmrateV> list = dataHarmRateVMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataHarmrateV>> lineMap = list.stream().collect(Collectors.groupingBy(DataHarmrateV::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataHarmrateV> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
+
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataHarmphasicVImpl.java

@@ -1,15 +1,25 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
-import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
+import cn.hutool.core.collection.CollectionUtil;
+import com.njcn.common.utils.HarmonicTimesUtil;
 import com.njcn.dataProcess.dao.imapper.DataHarmphasicVMapper;
+import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.influx.DataHarmphasicV;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.service.IDataHarmphasicV;
+import com.njcn.influx.constant.InfluxDbSqlConstant;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -23,6 +33,8 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataHarmphasicVImpl implements IDataHarmphasicV {
 
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
     private final DataHarmphasicVMapper dataHarmphasicVMapper;
 
 
@@ -44,4 +56,68 @@ public class InfluxdbDataHarmphasicVImpl implements IDataHarmphasicV {
 
         }
     }
+
+    @Override
+    public List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataHarmDto> result = new ArrayList<>();
+        List<DataHarmphasicV> list = getMinuteData(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataHarmDto dto = new DataHarmDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataHarmphasicV> getMinuteData(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataHarmphasicV> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataHarmphasicV.class);
+        influxQueryWrapper.samePrefixAndSuffix(InfluxDbSqlConstant.V, "", HarmonicTimesUtil.harmonicTimesList(1, 50, 1));
+        influxQueryWrapper.regular(DataHarmphasicV::getLineId, lineList)
+                .select(DataHarmphasicV::getLineId)
+                .select(DataHarmphasicV::getPhasicType)
+                .select(DataHarmphasicV::getValueType)
+                .select(DataHarmphasicV::getQualityFlag)
+                .between(DataHarmphasicV::getTime, startTime, endTime)
+                .eq(DataHarmphasicV::getQualityFlag,"0");
+        List<DataHarmphasicV> list = dataHarmphasicVMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataHarmphasicV>> lineMap = list.stream().collect(Collectors.groupingBy(DataHarmphasicV::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataHarmphasicV> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataHarmpowerPImpl.java

@@ -1,15 +1,28 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
+import cn.hutool.core.collection.CollectionUtil;
+import com.njcn.common.utils.HarmonicTimesUtil;
 import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
 import com.njcn.dataProcess.dao.imapper.DataHarmpowerPMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.influx.DataHarmpowerP;
+import com.njcn.dataProcess.po.influx.DataI;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
+import com.njcn.dataProcess.pojo.dto.DataPowerPDto;
 import com.njcn.dataProcess.service.IDataHarmpowerP;
+import com.njcn.influx.constant.InfluxDbSqlConstant;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
+import java.util.Collections;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -23,6 +36,8 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataHarmpowerPImpl implements IDataHarmpowerP {
 
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
     private final DataHarmpowerPMapper dataHarmpowerPMapper;
 
 
@@ -43,4 +58,71 @@ public class InfluxdbDataHarmpowerPImpl implements IDataHarmpowerP {
 
         }
     }
+
+    @Override
+    public List<DataPowerPDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataPowerPDto> result = new ArrayList<>();
+        List<DataHarmpowerP> list = getMinuteData(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataPowerPDto dto = new DataPowerPDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取dataI分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataHarmpowerP> getMinuteData(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataHarmpowerP> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataHarmpowerP.class);
+        influxQueryWrapper.samePrefixAndSuffix(InfluxDbSqlConstant.P, "", HarmonicTimesUtil.harmonicTimesList(1, 50, 1));
+        influxQueryWrapper.regular(DataHarmpowerP::getLineId, lineList)
+                .select(DataHarmpowerP::getLineId)
+                .select(DataHarmpowerP::getPhasicType)
+                .select(DataHarmpowerP::getValueType)
+                .select(DataHarmpowerP::getP)
+                .select(DataHarmpowerP::getDf)
+                .select(DataHarmpowerP::getPf)
+                .select(DataHarmpowerP::getQualityFlag)
+                .between(DataHarmpowerP::getTime, startTime, endTime)
+                .eq(DataHarmpowerP::getQualityFlag,"0");
+        List<DataHarmpowerP> list = dataHarmpowerPMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataHarmpowerP>> lineMap = list.stream().collect(Collectors.groupingBy(DataHarmpowerP::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataHarmpowerP> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataIImpl.java

@@ -1,15 +1,25 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
-import com.njcn.dataProcess.dto.DataIDTO;
+import cn.hutool.core.collection.CollectionUtil;
+import com.njcn.common.utils.HarmonicTimesUtil;
 import com.njcn.dataProcess.dao.imapper.DataIMapper;
+import com.njcn.dataProcess.dto.DataIDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.influx.DataI;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
 import com.njcn.dataProcess.service.IDataI;
+import com.njcn.influx.constant.InfluxDbSqlConstant;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -23,6 +33,8 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataIImpl implements IDataI {
 
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
     private final DataIMapper dataIMapper;
 
 
@@ -43,4 +55,75 @@ public class InfluxdbDataIImpl implements IDataI {
 
         }
     }
+
+    @Override
+    public List<DataIDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataIDto> result = new ArrayList<>();
+        List<DataI> list = getMinuteDataI(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataIDto dto = new DataIDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取dataI分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataI> getMinuteDataI(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataI> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataI.class);
+        influxQueryWrapper.samePrefixAndSuffix(InfluxDbSqlConstant.I, "", HarmonicTimesUtil.harmonicTimesList(1, 50, 1));
+        influxQueryWrapper.regular(DataI::getLineId, lineList)
+                .select(DataI::getLineId)
+                .select(DataI::getPhasicType)
+                .select(DataI::getValueType)
+                .select(DataI::getINeg)
+                .select(DataI::getIPos)
+                .select(DataI::getIThd)
+                .select(DataI::getIUnbalance)
+                .select(DataI::getIZero)
+                .select(DataI::getRms)
+                .select(DataI::getQualityFlag)
+                .between(DataI::getTime, startTime, endTime)
+                .eq(DataI::getQualityFlag,"0");
+        List<DataI> list = dataIMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataI>> lineMap = list.stream().collect(Collectors.groupingBy(DataI::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataI> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
+
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataInharmVImpl.java

@@ -1,17 +1,29 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
-import com.njcn.dataProcess.dto.DataInharmVDTO;
+import cn.hutool.core.collection.CollectionUtil;
+import com.njcn.common.utils.HarmonicTimesUtil;
 import com.njcn.dataProcess.dao.imapper.DataInharmVMapper;
+import com.njcn.dataProcess.dto.DataInharmVDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.po.influx.DataI;
 import com.njcn.dataProcess.po.influx.DataInharmV;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.service.IDataInharmV;
+import com.njcn.influx.constant.InfluxDbSqlConstant;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
+
 /**
  * Description:
  * Date: 2024/11/18  14:33【需求编号】
@@ -23,6 +35,8 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataInharmVImpl implements IDataInharmV {
 
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
+
     private final DataInharmVMapper dataInharmVMapper;
 
 
@@ -43,4 +57,68 @@ public class InfluxdbDataInharmVImpl implements IDataInharmV {
 
         }
     }
+
+    @Override
+    public List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataHarmDto> result = new ArrayList<>();
+        List<DataInharmV> list = getMinuteData(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataHarmDto dto = new DataHarmDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取dataI分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataInharmV> getMinuteData(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataInharmV> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataInharmV.class);
+        influxQueryWrapper.samePrefixAndSuffix(InfluxDbSqlConstant.V, "", HarmonicTimesUtil.harmonicTimesList(1, 50, 1));
+        influxQueryWrapper.regular(DataInharmV::getLineId, lineList)
+                .select(DataInharmV::getLineId)
+                .select(DataInharmV::getPhasicType)
+                .select(DataInharmV::getValueType)
+                .select(DataInharmV::getQualityFlag)
+                .between(DataI::getTime, startTime, endTime)
+                .eq(DataI::getQualityFlag,"0");
+        List<DataInharmV> list = dataInharmVMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataInharmV>> lineMap = list.stream().collect(Collectors.groupingBy(DataInharmV::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataInharmV> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataPltImpl.java

@@ -1,15 +1,26 @@
 package com.njcn.dataProcess.service.impl.influxdb;
 
-import com.njcn.dataProcess.dto.DataPltDTO;
+import cn.hutool.core.collection.CollectionUtil;
+import com.njcn.common.utils.HarmonicTimesUtil;
 import com.njcn.dataProcess.dao.imapper.DataPltMapper;
+import com.njcn.dataProcess.dto.DataPltDTO;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.po.influx.DataI;
 import com.njcn.dataProcess.po.influx.DataPlt;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 import com.njcn.dataProcess.service.IDataPlt;
+import com.njcn.influx.constant.InfluxDbSqlConstant;
+import com.njcn.influx.query.InfluxQueryWrapper;
 import lombok.RequiredArgsConstructor;
 import org.apache.commons.collections4.ListUtils;
+import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
@@ -23,8 +34,9 @@ import java.util.stream.Collectors;
 @RequiredArgsConstructor
 public class InfluxdbDataPltImpl implements IDataPlt {
 
-    private final DataPltMapper dataPltMapper;
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
 
+    private final DataPltMapper dataPltMapper;
 
     @Override
     public void batchInsertion(List<DataPltDTO> dataPltDTOList) {
@@ -44,4 +56,68 @@ public class InfluxdbDataPltImpl implements IDataPlt {
 
         }
     }
+
+    @Override
+    public List<DataPltDto> getRawData(LineCountEvaluateParam lineParam) {
+        List<DataPltDto> result = new ArrayList<>();
+        List<DataPlt> list = getMinuteDataPlt(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
+        list.forEach(item->{
+            DataPltDto dto = new DataPltDto();
+            BeanUtils.copyProperties(item,dto);
+            dto.setMinTime(DATE_TIME_FORMATTER.format(item.getTime()));
+            result.add(dto);
+        });
+        return result;
+    }
+
+    /**
+     * 按监测点集合、时间条件获取dataI分钟数据
+     * timeMap参数来判断是否进行数据处理 timeMap为空则不进行数据处理
+     * 需要进行剔除异常数据时,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
+     */
+    public List<DataPlt> getMinuteDataPlt(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataPlt> result = new ArrayList<>();
+        InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataPlt.class);
+        influxQueryWrapper.regular(DataPlt::getLineId, lineList)
+                .select(DataPlt::getLineId)
+                .select(DataPlt::getPhasicType)
+                .select(DataPlt::getPlt)
+                .select(DataPlt::getQualityFlag)
+                .between(DataPlt::getTime, startTime, endTime)
+                .eq(DataPlt::getQualityFlag,"0");
+        List<DataPlt> list = dataPltMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataPlt>> lineMap = list.stream().collect(Collectors.groupingBy(DataPlt::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,当前监测点自身的异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataPlt> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
+        }
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
+    }
+
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbDataVImpl.java

@@ -29,6 +29,7 @@ import java.time.LocalDateTime;
 import java.time.ZoneId;
 import java.time.format.DateTimeFormatter;
 import java.util.*;
+import java.util.function.Function;
 import java.util.stream.Collectors;
 
 /**
@@ -39,7 +40,7 @@ import java.util.stream.Collectors;
 @Service("InfluxdbDataVImpl")
 public class InfluxdbDataVImpl extends MppServiceImpl<RStatDataVRelationMapper, RStatDataVD> implements IDataV {
 
-    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());;
+    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss").withZone(ZoneId.systemDefault());
 
     @Resource
     private DataVMapper dataVMapper;
@@ -119,7 +120,7 @@ public class InfluxdbDataVImpl extends MppServiceImpl<RStatDataVRelationMapper,
     @Override
     public List<DataVDto> getRawData(LineCountEvaluateParam lineParam) {
         List<DataVDto> result = new ArrayList<>();
-        List<DataV> list = getMinuteDataV(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), false);
+        List<DataV> list = getMinuteDataV(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(), lineParam.getAbnormalTime());
         list.forEach(item->{
             DataVDto dto = new DataVDto();
             BeanUtils.copyProperties(item,dto);
@@ -132,7 +133,7 @@ public class InfluxdbDataVImpl extends MppServiceImpl<RStatDataVRelationMapper,
     @Override
     public List<CommonMinuteDto> getBaseData(LineCountEvaluateParam lineParam) {
         List<CommonMinuteDto> result = new ArrayList<>();
-        List<DataV> dataVList = getMinuteDataV(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(),true);
+        List<DataV> dataVList = getMinuteDataV(lineParam.getLineId(), lineParam.getStartTime(), lineParam.getEndTime(),lineParam.getAbnormalTime());
         if (CollectionUtil.isNotEmpty(dataVList)) {
             String time = TimeUtils.StringTimeToString(lineParam.getStartTime());
             //以监测点分组
@@ -141,6 +142,7 @@ public class InfluxdbDataVImpl extends MppServiceImpl<RStatDataVRelationMapper,
                 CommonMinuteDto dto = new CommonMinuteDto();
                 dto.setLineId(line);
                 dto.setTime(time);
+                dto.setQualityFlag(lineList.get(0).getQualityFlag());
                 //以相别分组
                 Map<String,List<DataV>> phasicTypeMap = lineList.stream().collect(Collectors.groupingBy(DataV::getPhasicType));
                 List<CommonMinuteDto.PhasicType> phasicTypes = new ArrayList<>();
@@ -256,8 +258,14 @@ public class InfluxdbDataVImpl extends MppServiceImpl<RStatDataVRelationMapper,
 
     /**
      * 按监测点集合、时间条件获取dataV分钟数据
+     * timeMap参数来判断是否进行数据出来 timeMap为空则不进行数据处理
+     * 剔除异常数据,这里会有三种情况判断
+     * 1.无异常数据，则直接返回集合；
+     * 2.异常数据和无异常数据参杂，剔除异常数据，只计算正常数据；
+     * 3.全是异常数据，则使用异常数据进行计算，但是日表中需要标记出来，此数据有异常
      */
-    public List<DataV> getMinuteDataV(List<String> lineList, String startTime, String endTime, boolean clean) {
+    public List<DataV> getMinuteDataV(List<String> lineList, String startTime, String endTime, Map<String,List<String>> timeMap) {
+        List<DataV> result = new ArrayList<>();
         InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataV.class);
         influxQueryWrapper.samePrefixAndSuffix(InfluxDbSqlConstant.V, "", HarmonicTimesUtil.harmonicTimesList(1, 50, 1));
         influxQueryWrapper.regular(DataV::getLineId, lineList)
@@ -276,11 +284,38 @@ public class InfluxdbDataVImpl extends MppServiceImpl<RStatDataVRelationMapper,
                 .select(DataV::getVlDev)
                 .select(DataV::getVuDev)
                 .select(DataV::getQualityFlag)
-                .between(DataV::getTime, startTime, endTime);
-        if (clean) {
-            influxQueryWrapper.eq(DataV::getAbnormalFlag,0);
+                .between(DataV::getTime, startTime, endTime)
+                .eq(DataV::getQualityFlag,"0");
+        List<DataV> list = dataVMapper.selectByQueryWrapper(influxQueryWrapper);
+        Map<String,List<DataV>> lineMap = list.stream().collect(Collectors.groupingBy(DataV::getLineId));
+        //有异常数据
+        if (CollectionUtil.isNotEmpty(timeMap)) {
+            lineMap.forEach((k,v)->{
+                List<String> timeList = timeMap.get(k);
+                //有异常数据,是自身异常数据
+                if (CollectionUtil.isNotEmpty(timeList)) {
+                    List<DataV> filterList = v.stream().filter(item -> !timeList.contains(DATE_TIME_FORMATTER.format(item.getTime()))).collect(Collectors.toList());
+                    //1.过滤掉异常数据后还有正常数据，则用正常数据计算
+                    if (CollectionUtil.isNotEmpty(filterList)) {
+                        result.addAll(filterList);
+                    }
+                    //2.过滤掉异常数据后没有正常数据，则用所有异常数据计算，但是需要标记数据为异常的
+                    else {
+                        v.parallelStream().forEach(item -> item.setQualityFlag("1"));
+                        result.addAll(v);
+                    }
+                }
+                //没有异常数据，则使用原数据
+                else {
+                    result.addAll(v);
+                }
+            });
         }
-        return dataVMapper.selectByQueryWrapper(influxQueryWrapper);
+        //没有异常数据，则使用原数据
+        else {
+            result.addAll(list);
+        }
+        return result;
     }
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/PqDataVerifyServiceImpl.java

@@ -0,0 +1,46 @@
+package com.njcn.dataProcess.service.impl.relation;
+
+import cn.hutool.core.collection.CollUtil;
+import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
+import com.github.jeffreyning.mybatisplus.service.MppServiceImpl;
+import com.njcn.dataProcess.dao.relation.mapper.PqDataVerifyMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.po.PqDataVerify;
+import com.njcn.dataProcess.service.IPqDataVerifyService;
+import org.springframework.stereotype.Service;
+import org.springframework.transaction.annotation.Transactional;
+
+import java.util.List;
+import java.util.Objects;
+
+/**
+ * <p>
+ *  服务实现类
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-17
+ */
+@Service
+public class PqDataVerifyServiceImpl extends MppServiceImpl<PqDataVerifyMapper, PqDataVerify> implements IPqDataVerifyService {
+
+    @Override
+    @Transactional(rollbackFor = Exception.class)
+    public void insertData(List<PqDataVerify> list) {
+        this.saveOrUpdateBatchByMultiId(list);
+    }
+
+    @Override
+    public List<PqDataVerify> queryData(LineCountEvaluateParam param) {
+        LambdaQueryWrapper<PqDataVerify> queryWrapper = new LambdaQueryWrapper<>();
+        queryWrapper.between(PqDataVerify::getTime,param.getStartTime(),param.getEndTime());
+        if (CollUtil.isNotEmpty(param.getLineId())) {
+            queryWrapper.in(PqDataVerify::getLineId,param.getLineId());
+        }
+        if (!Objects.isNull(param.getTableName())) {
+            queryWrapper.eq(PqDataVerify::getIndexTable, param.getTableName());
+        }
+        return this.list(queryWrapper);
+    }
+
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/PqReasonableRangeServiceImpl.java

@@ -0,0 +1,46 @@
+package com.njcn.dataProcess.service.impl.relation;
+
+import cn.hutool.core.collection.CollUtil;
+import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
+import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
+import com.njcn.dataProcess.dao.relation.mapper.PqReasonableRangeMapper;
+import com.njcn.dataProcess.param.DataCleanParam;
+import com.njcn.dataProcess.pojo.dto.PqReasonableRangeDto;
+import com.njcn.dataProcess.pojo.po.PqReasonableRange;
+import com.njcn.dataProcess.service.IPqReasonableRangeService;
+import org.springframework.beans.BeanUtils;
+import org.springframework.stereotype.Service;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * <p>
+ *  服务实现类
+ * </p>
+ *
+ * @author xy
+ * @since 2025-02-13
+ */
+@Service
+public class PqReasonableRangeServiceImpl extends ServiceImpl<PqReasonableRangeMapper, PqReasonableRange> implements IPqReasonableRangeService {
+
+    @Override
+    public List<PqReasonableRangeDto> getReasonableRangeList(DataCleanParam param) {
+        List<PqReasonableRangeDto> result = new ArrayList<>();
+        LambdaQueryWrapper<PqReasonableRange> queryWrapper = new LambdaQueryWrapper<>();
+        queryWrapper.eq(PqReasonableRange::getBelongingSystem,param.getSystemType())
+                .eq(PqReasonableRange::getDataSource,param.getDataSource())
+                .eq(PqReasonableRange::getInfluxdbTableName,param.getTableName())
+                .eq(PqReasonableRange::getState,1);
+        List<PqReasonableRange> list = this.list(queryWrapper);
+        if (CollUtil.isNotEmpty(list)) {
+            list.forEach(item->{
+                PqReasonableRangeDto dto = new PqReasonableRangeDto();
+                BeanUtils.copyProperties(item,dto);
+                result.add(dto);
+            });
+        }
+        return result;
+    }
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataFlickerImpl.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.service.impl.relation;
 import com.njcn.dataProcess.dto.DataFlickerDTO;
 
 import com.njcn.dataProcess.dao.relation.mapper.DataFlickerRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataFlicker;
+import com.njcn.dataProcess.pojo.dto.DataFlickerDto;
 import com.njcn.dataProcess.service.IDataFlicker;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -11,6 +13,7 @@ import org.apache.commons.collections4.ListUtils;
 import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -53,4 +56,9 @@ public class RelationDataFlickerImpl implements IDataFlicker {
         }
 
     }
+
+    @Override
+    public List<DataFlickerDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataFlucImpl.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.service.impl.relation;
 import com.njcn.dataProcess.dto.DataFlucDTO;
 
 import com.njcn.dataProcess.dao.relation.mapper.DataFlucRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataFluc;
+import com.njcn.dataProcess.pojo.dto.DataFlucDto;
 import com.njcn.dataProcess.service.IDataFluc;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -11,6 +13,7 @@ import org.apache.commons.collections4.ListUtils;
 import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -43,5 +46,12 @@ public class RelationDataFlucImpl implements IDataFluc {
             dataFlucRelationMapper.insertBatchSomeColumn(dataFlucList);
 
         }
-    };
+    }
+
+    @Override
+    public List<DataFlucDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
+
+    ;
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataHarmRateVImpl.java

@@ -0,0 +1,28 @@
+package com.njcn.dataProcess.service.impl.relation;
+
+import com.njcn.dataProcess.dao.relation.mapper.DataIRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
+import com.njcn.dataProcess.service.IDataHarmRateV;
+import lombok.RequiredArgsConstructor;
+import org.springframework.stereotype.Service;
+
+import javax.annotation.Resource;
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * @author xy
+ */
+@Service("RelationDataHarmRateVImpl")
+@RequiredArgsConstructor
+public class RelationDataHarmRateVImpl implements IDataHarmRateV {
+
+    @Resource
+    private DataIRelationMapper dataIRelationMapper;
+
+    @Override
+    public List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
+}

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataHarmphasicVImpl.java

@@ -2,7 +2,9 @@ package com.njcn.dataProcess.service.impl.relation;
 
 import com.njcn.dataProcess.dto.DataHarmphasicVDTO;
 import com.njcn.dataProcess.dao.relation.mapper.DataHarmphasicVRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataHarmphasicV;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.service.IDataHarmphasicV;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -10,6 +12,7 @@ import org.apache.commons.collections4.ListUtils;
 import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -50,5 +53,10 @@ public class RelationDataHarmphasicVImpl implements IDataHarmphasicV {
         }
     }
 
+    @Override
+    public List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
+
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataHarmpowerPImpl.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.service.impl.relation;
 import com.njcn.dataProcess.dto.DataHarmpowerPDTO;
 
 import com.njcn.dataProcess.dao.relation.mapper.DataHarmpowerPRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataHarmpowerP;
+import com.njcn.dataProcess.pojo.dto.DataPowerPDto;
 import com.njcn.dataProcess.service.IDataHarmpowerP;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -11,6 +13,7 @@ import org.apache.commons.collections4.ListUtils;
 import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -53,4 +56,9 @@ public class RelationDataHarmpowerPImpl implements IDataHarmpowerP {
 
         }
     }
+
+    @Override
+    public List<DataPowerPDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataIImpl.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.service.impl.relation;
 import com.njcn.dataProcess.dto.DataIDTO;
 
 import com.njcn.dataProcess.dao.relation.mapper.DataIRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataI;
+import com.njcn.dataProcess.pojo.dto.DataIDto;
 import com.njcn.dataProcess.service.IDataI;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -12,6 +14,7 @@ import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
 import javax.annotation.Resource;
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -51,4 +54,9 @@ public class RelationDataIImpl implements IDataI {
             dataIRelationMapper.insertBatchSomeColumn(dataIList);
         }
     }
+
+    @Override
+    public List<DataIDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataInharmVImpl.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.service.impl.relation;
 import com.njcn.dataProcess.dto.DataInharmVDTO;
 
 import com.njcn.dataProcess.dao.relation.mapper.DataVInharmVRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataInharmV;
+import com.njcn.dataProcess.pojo.dto.DataHarmDto;
 import com.njcn.dataProcess.service.IDataInharmV;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -11,6 +13,7 @@ import org.apache.commons.collections4.ListUtils;
 import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -51,4 +54,9 @@ public class RelationDataInharmVImpl implements IDataInharmV {
         }
 
     }
+
+    @Override
+    public List<DataHarmDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataPltImpl.java

@@ -3,7 +3,9 @@ package com.njcn.dataProcess.service.impl.relation;
 import com.njcn.dataProcess.dto.DataPltDTO;
 
 import com.njcn.dataProcess.dao.relation.mapper.DataPltRelationMapper;
+import com.njcn.dataProcess.param.LineCountEvaluateParam;
 import com.njcn.dataProcess.po.relation.DataPlt;
+import com.njcn.dataProcess.pojo.dto.DataPltDto;
 import com.njcn.dataProcess.service.IDataPlt;
 import com.njcn.dataProcess.util.BeanFeildUtils;
 import lombok.RequiredArgsConstructor;
@@ -11,6 +13,7 @@ import org.apache.commons.collections4.ListUtils;
 import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
+import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
@@ -51,4 +54,9 @@ public class RelationDataPltImpl implements IDataPlt {
             dataPltRelationMapper.insertBatchSomeColumn(dataPltList);
         }
     }
+
+    @Override
+    public List<DataPltDto> getRawData(LineCountEvaluateParam lineParam) {
+        return Collections.emptyList();
+    }
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/relation/RelationDataVImpl.java

@@ -2,6 +2,7 @@ package com.njcn.dataProcess.service.impl.relation;
 
 import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
 import com.github.jeffreyning.mybatisplus.service.MppServiceImpl;
+import com.njcn.dataProcess.annotation.InsertBean;
 import com.njcn.dataProcess.dao.relation.mapper.DataVRelationMapper;
 import com.njcn.dataProcess.dao.relation.mapper.RStatDataVRelationMapper;
 import com.njcn.dataProcess.dto.DataVDTO;
@@ -20,6 +21,7 @@ import org.springframework.beans.BeanUtils;
 import org.springframework.stereotype.Service;
 
 import javax.annotation.Resource;
+import java.lang.reflect.Field;
 import java.time.LocalDateTime;
 import java.util.ArrayList;
 import java.util.Collections;
@@ -37,8 +39,11 @@ import java.util.stream.Collectors;
 public class RelationDataVImpl extends MppServiceImpl<RStatDataVRelationMapper, RStatDataVD> implements IDataV {
     @Resource
     private DataVRelationMapper dataVRelationMapper;
+
     @Resource
+    @InsertBean
     private IDataV iDataV;
+
     @Override
     public Map<String, List<DataVFiveItemDTO>> getLineCountEvaluate(LineCountEvaluateParam lineParam) {
 
@@ -100,10 +105,11 @@ public class RelationDataVImpl extends MppServiceImpl<RStatDataVRelationMapper,
             RStatDataVD dataV = new RStatDataVD();
             dataV.setTime(TimeUtils.LocalDataTimeToLocalDate2(item.getTime()));
             dataV.setPhasicType(item.getPhasicType());
+            dataV.setQualityFlag(Integer.valueOf(item.getQualityFlag()));
             BeanUtils.copyProperties(item, dataV);
             result.add(dataV);
         });
-        iDataV.saveOrUpdateBatch(result);
+        iDataV.saveOrUpdateBatchByMultiId(result);
     }
 
     @Override