ansteel-biz/src/main/java/com/iailab/module/ansteel/job/task/RunCokingTraceModelHCTask.java

@@ -8,6 +8,8 @@
import com.iailab.module.ansteel.coking.service.*;
import com.iailab.module.ansteel.common.constant.CommonConstant;
import com.iailab.module.ansteel.common.enums.TraceProcessTypeEnum;
import com.iailab.module.model.api.mcs.McsApi;
import com.iailab.module.model.api.mdk.dto.StScheduleRecordVO;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
@@ -49,6 +51,9 @@
    @Autowired
    private CokingTraceConfService cokingTraceConfService;

    @Autowired
    private McsApi mcsApi;

    private final static String process = TraceProcessTypeEnum.HC.getProcess();

    private final static String reportName = "化产工序异常溯源";
@@ -57,23 +62,9 @@

    private final static String indType = "化产工序异常溯源";

    private final static String row = "chemProdRow";

    private final static String total = "chemProdTotal";

    private static final String jsonStr = "{\n" +
            "\"result\":{\n" +
            "\"chemProdHomePage\":[1782.7,0.8]," +
            "\"chemProdElec\":[794680.52]," +
            "\"chemProdIndex\":[16.3,2.57,0.017,0.745,658731.5]," +
            "\"chemProdRow0\":[[0.0,42.3],[5.0,1342.5],[10.0,122.5]]," +
            "\"chemProdRow1\":[[0.0,42.3],[7.0,12.5],[9.0,17.45]]," +
            "\"chemProdRow2\":[[0.0,42.3],[12.0,23.5],[35.0,54.33]]," +
            "\"chemProdSteam\":[46.3]," +
            "\"chemProdTotal\":\"蒸汽消耗量异常，经模型计算，原因和调整建议如下：电捕绝缘箱温度异常，当前值190，建议调整电捕绝缘箱温度至区间[80,110], 蒸氨塔塔顶温度异常，当前值190，建议调整蒸氨塔塔顶温度至区间[101,103]\"," +
            "\"chemProdHomeIndexInfo\":\"化产蒸汽消耗量异常\""+
            " }" +
            "}";
    private String scheduleCode = "AnSteelChemProSteamTrack"; //焦化化产蒸汽消耗模型
    private final String finalResultStrKey = "finalResultStr";
    private final String resultListKey = "resultList";

    @Override
    public void run(String params) {
@@ -99,20 +90,20 @@
            calendar.set(Calendar.HOUR_OF_DAY, 0);//化产折线图用的时间 前七天
            Date chartStartDate = calendar.getTime();

            // 调用模型
//            MdkScheduleReqDTO dto = new MdkScheduleReqDTO();
//            dto.setScheduleTime(calendar.getTime());
//            dto.setScheduleCode(params);
//            MdkScheduleRespDTO mdkScheduleRespDTO = mdkApi.doSchedule(dto);
//            logger.info(params + "调度方案执行完成，" + mdkScheduleRespDTO);
//
//            Map<String, Object> tResult = mdkScheduleRespDTO.getResult();
//            JSONObject result = new JSONObject(tResult);
//            logger.info("result===" +  JSONObject.toJSONString(result));
            // 查询模型结果
            List<StScheduleRecordVO> lastScheduleData = mcsApi.getLastScheduleData(scheduleCode, 1);
            if (CollectionUtils.isEmpty(lastScheduleData)) {
                logger.info("模型结果为空");
                return;
            }
            StScheduleRecordVO stScheduleRecordVO = lastScheduleData.get(0);
            if (stScheduleRecordVO == null) {
                logger.info("模型结果为空");
                return;
            }
            String jsonStr = stScheduleRecordVO.getResultData();

            JSONObject jsonObject = JSONObject.parseObject(jsonStr);
            JSONObject result = (JSONObject) JSON.toJSON(jsonObject.get("result"));

            JSONObject result = JSONObject.parseObject(jsonStr);
            if (Objects.isNull(result)) {
                logger.info("模型结果为空");
                return;
@@ -120,18 +111,19 @@

            // 保存报告
            String analyDate = DateUtils.format(startDate);
            String analyContent = clock + " " + result.getString("chemProdHomeIndexInfo");
            String content = result.getString(total);
            String analyContent = "化产异常";
            String relId = cokingTraceReportService.save(process, reportName, analyDate, clock, analyContent);

            // 保存一级分析指标
            cokingAnalyIndService.saveAnalyInd(relId, process, analyDate, analyContent);

            // 保存优化建议
            cokingTraceSuggestService.saveTraceSuggest(relId, process, clock, content, SugObj);
            String suggest = result.getString(finalResultStrKey);
            cokingTraceSuggestService.saveTraceSuggest(relId, process, clock, suggest, SugObj);

            // 保存偏差值
            cokingTraceDeviationService.saveTraceDeviation(relId, process, clock, result, CommonConstant.COKE_INDEX_CHARTCODE, row, SugObj);
            String jsonString = result.getString(resultListKey);
            cokingTraceDeviationService.saveTraceDeviation(relId, process, clock, jsonString, SugObj);

            // 保存溯源指标
            cokingTraceIndService.saveTraceInd(relId, indType, clock,collectStartDate,endDate);