ansteel-biz/db/mysql.sql

@@ -560,38 +560,82 @@
-- 焦化工序-影响因数偏差值
-- ----------------------------
DROP TABLE IF EXISTS `t_coking_trace_deviation`;
CREATE TABLE `t_coking_trace_deviation`
(
    `id`          varchar(36) NOT NULL COMMENT 'id',
    `rel_id`      varchar(36) NULL DEFAULT NULL COMMENT '关联ID',
    `process`     varchar(20) NULL DEFAULT NULL COMMENT '工序名称',
    `sug_obj`     varchar(20) NULL DEFAULT NULL COMMENT '建议对象',
    `clock`       varchar(20) NULL DEFAULT NULL COMMENT '查询时间',
    `ind1_name`   varchar(20) NULL DEFAULT NULL COMMENT '一级指标-偏差值-名称',
    `ind1_value`  varchar(20) NULL DEFAULT NULL COMMENT '一级指标-偏差值-值',
    `ind1_unit`   varchar(20) NULL DEFAULT NULL COMMENT '一级指标-偏差值-单位',
    `ind2_name`   varchar(20) NULL DEFAULT NULL COMMENT '二级指标-偏差值-名称',
    `ind2_value`  varchar(20) NULL DEFAULT NULL COMMENT '二级指标-偏差值-值',
    `ind2_unit`   varchar(20) NULL DEFAULT NULL COMMENT '二级指标-偏差值-单位',
    `fac1_name`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素1-偏差值-名称',
    `fac1_value`  varchar(20) NULL DEFAULT NULL COMMENT '影响因素1-偏差值-值',
    `fac1_unit`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素1-偏差值-单位',
    `fac2_name`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素2-偏差值-名称',
    `fac2_value`  varchar(20) NULL DEFAULT NULL COMMENT '影响因素2-偏差值-值',
    `fac2_unit`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素2-偏差值-单位',
    `fac3_name`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素3-偏差值-名称',
    `fac3_value`  varchar(20) NULL DEFAULT NULL COMMENT '影响因素3-偏差值-值',
    `fac3_unit`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素4-偏差值-单位',
    `fac4_name`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素4-偏差值-名称',
    `fac4_value`  varchar(20) NULL DEFAULT NULL COMMENT '影响因素4-偏差值-值',
    `fac4_unit`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素4-偏差值-单位',
    `fac5_name`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素5-偏差值-名称',
    `fac5_value`  varchar(20) NULL DEFAULT NULL COMMENT '影响因素5-偏差值-值',
    `fac5_unit`   varchar(20) NULL DEFAULT NULL COMMENT '影响因素5-偏差值-单位',
    `create_date` datetime COMMENT '创建时间',
    PRIMARY KEY (`id`) USING BTREE,
    key           idx_clock (clock)
) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = DYNAMIC COMMENT '焦化工序影响因数偏差值';
CREATE TABLE `t_coking_trace_deviation` (
                                            `id` varchar(36) COLLATE utf8mb4_general_ci NOT NULL COMMENT 'id',
                                            `rel_id` varchar(36) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '关联ID',
                                            `process` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '工序名称',
                                            `sug_obj` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '建议对象',
                                            `clock` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '查询时间',
                                            `ind1_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '一级指标-偏差值-名称',
                                            `ind1_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '一级指标-偏差值-值',
                                            `ind1_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '一级指标-偏差值-单位',
                                            `ind2_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '二级指标-偏差值-名称',
                                            `ind2_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '二级指标-偏差值-值',
                                            `ind2_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '二级指标-偏差值-单位',
                                            `fac1_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素1-偏差值-名称',
                                            `fac1_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素1-偏差值-值',
                                            `fac1_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素1-偏差值-单位',
                                            `fac2_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素2-偏差值-名称',
                                            `fac2_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素2-偏差值-值',
                                            `fac2_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素2-偏差值-单位',
                                            `fac3_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素3-偏差值-名称',
                                            `fac3_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素3-偏差值-值',
                                            `fac3_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素4-偏差值-单位',
                                            `fac4_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素4-偏差值-名称',
                                            `fac4_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素4-偏差值-值',
                                            `fac4_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素4-偏差值-单位',
                                            `fac5_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素5-偏差值-名称',
                                            `fac5_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素5-偏差值-值',
                                            `fac5_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素5-偏差值-单位',
                                            `fac6_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素6-偏差值-名称',
                                            `fac6_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素6-偏差值-值',
                                            `fac6_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素6-偏差值-单位',
                                            `fac7_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素7-偏差值-名称',
                                            `fac7_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素7-偏差值-值',
                                            `fac7_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素7-偏差值-单位',
                                            `fac8_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素8-偏差值-名称',
                                            `fac8_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素8-偏差值-值',
                                            `fac8_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素8-偏差值-单位',
                                            `fac9_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素9-偏差值-名称',
                                            `fac9_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素9-偏差值-值',
                                            `fac9_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素9-偏差值-单位',
                                            `fac10_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素10-偏差值-名称',
                                            `fac10_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素10-偏差值-值',
                                            `fac10_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素10-偏差值-单位',
                                            `fac11_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素11-偏差值-名称',
                                            `fac11_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素11-偏差值-值',
                                            `fac11_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素11-偏差值-单位',
                                            `fac12_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素12-偏差值-名称',
                                            `fac12_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素12-偏差值-值',
                                            `fac12_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素12-偏差值-单位',
                                            `fac13_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素13-偏差值-名称',
                                            `fac13_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素13-偏差值-值',
                                            `fac13_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素13-偏差值-单位',
                                            `fac14_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素14-偏差值-名称',
                                            `fac14_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素14-偏差值-值',
                                            `fac14_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素14-偏差值-单位',
                                            `fac15_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素15-偏差值-名称',
                                            `fac15_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素15-偏差值-值',
                                            `fac15_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素15-偏差值-单位',
                                            `fac16_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素16-偏差值-名称',
                                            `fac16_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素16-偏差值-值',
                                            `fac16_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素16-偏差值-单位',
                                            `fac17_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素17-偏差值-名称',
                                            `fac17_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素17-偏差值-值',
                                            `fac17_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素17-偏差值-单位',
                                            `fac18_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素18-偏差值-名称',
                                            `fac18_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素18-偏差值-值',
                                            `fac18_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素18-偏差值-单位',
                                            `fac19_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素19-偏差值-名称',
                                            `fac19_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素19-偏差值-值',
                                            `fac19_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素19-偏差值-单位',
                                            `fac20_name` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素20-偏差值-名称',
                                            `fac20_value` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素20-偏差值-值',
                                            `fac20_unit` varchar(20) COLLATE utf8mb4_general_ci DEFAULT NULL COMMENT '影响因素20-偏差值-单位',
                                            `create_date` datetime DEFAULT NULL COMMENT '创建时间',
                                            PRIMARY KEY (`id`) USING BTREE,
                                            KEY `idx_clock` (`clock`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_general_ci ROW_FORMAT=DYNAMIC COMMENT='焦化工序影响因数偏差值';


-- ----------------------------

 ansteel-biz/src/main/java/com/iailab/module/ansteel/coking/dto/CokingTraceDeviationDTO.java

@@ -96,6 +96,141 @@
    @Schema(description = "影响因素5-偏差值-单位")
    private String fac5Unit;

    @Schema(description = "影响因素6-偏差值-名称")
    private String fac6Name;

    @Schema(description = "影响因素6-偏差值-值")
    private String fac6Value;

    @Schema(description = "影响因素6-偏差值-单位")
    private String fac6Unit;

    @Schema(description = "影响因素7-偏差值-名称")
    private String fac7Name;

    @Schema(description = "影响因素7-偏差值-值")
    private String fac7Value;

    @Schema(description = "影响因素7-偏差值-单位")
    private String fac7Unit;

    @Schema(description = "影响因素8-偏差值-名称")
    private String fac8Name;

    @Schema(description = "影响因素8-偏差值-值")
    private String fac8Value;

    @Schema(description = "影响因素8-偏差值-单位")
    private String fac8Unit;

    @Schema(description = "影响因素9-偏差值-名称")
    private String fac9Name;

    @Schema(description = "影响因素9-偏差值-值")
    private String fac9Value;

    @Schema(description = "影响因素9-偏差值-单位")
    private String fac9Unit;

    @Schema(description = "影响因素10-偏差值-名称")
    private String fac10Name;

    @Schema(description = "影响因素10-偏差值-值")
    private String fac10Value;

    @Schema(description = "影响因素10-偏差值-单位")
    private String fac10Unit;

    @Schema(description = "影响因素11-偏差值-名称")
    private String fac11Name;

    @Schema(description = "影响因素11-偏差值-值")
    private String fac11Value;

    @Schema(description = "影响因素11-偏差值-单位")
    private String fac11Unit;

    @Schema(description = "影响因素12-偏差值-名称")
    private String fac12Name;

    @Schema(description = "影响因素12-偏差值-值")
    private String fac12Value;

    @Schema(description = "影响因素12-偏差值-单位")
    private String fac12Unit;

    @Schema(description = "影响因素13-偏差值-名称")
    private String fac13Name;

    @Schema(description = "影响因素13-偏差值-值")
    private String fac13Value;

    @Schema(description = "影响因素13-偏差值-单位")
    private String fac13Unit;

    @Schema(description = "影响因素14-偏差值-名称")
    private String fac14Name;

    @Schema(description = "影响因素14-偏差值-值")
    private String fac14Value;

    @Schema(description = "影响因素14-偏差值-单位")
    private String fac14Unit;

    @Schema(description = "影响因素15-偏差值-名称")
    private String fac15Name;

    @Schema(description = "影响因素15-偏差值-值")
    private String fac15Value;

    @Schema(description = "影响因素15-偏差值-单位")
    private String fac15Unit;

    @Schema(description = "影响因素16-偏差值-名称")
    private String fac16Name;

    @Schema(description = "影响因素16-偏差值-值")
    private String fac16Value;

    @Schema(description = "影响因素16-偏差值-单位")
    private String fac16Unit;

    @Schema(description = "影响因素17-偏差值-名称")
    private String fac17Name;

    @Schema(description = "影响因素17-偏差值-值")
    private String fac17Value;

    @Schema(description = "影响因素17-偏差值-单位")
    private String fac17Unit;

    @Schema(description = "影响因素18-偏差值-名称")
    private String fac18Name;

    @Schema(description = "影响因素18-偏差值-值")
    private String fac18Value;

    @Schema(description = "影响因素18-偏差值-单位")
    private String fac18Unit;

    @Schema(description = "影响因素19-偏差值-名称")
    private String fac19Name;

    @Schema(description = "影响因素19-偏差值-值")
    private String fac19Value;

    @Schema(description = "影响因素19-偏差值-单位")
    private String fac19Unit;

    @Schema(description = "影响因素20-偏差值-名称")
    private String fac20Name;

    @Schema(description = "影响因素20-偏差值-值")
    private String fac20Value;

    @Schema(description = "影响因素20-偏差值-单位")
    private String fac20Unit;

    @Schema(description = "创建时间")
    private Date createDate;


 ansteel-biz/src/main/java/com/iailab/module/ansteel/coking/entity/CokingTraceDeviationEntity.java

@@ -127,6 +127,200 @@
     */
    private String fac5Unit;

    /**
     * 影响因素6-偏差值-名称
     */
    private String fac6Name;
    /**
     * 影响因素6-偏差值-值
     */
    private String fac6Value;
    /**
     * 影响因素6-偏差值-单位
     */
    private String fac6Unit;

    /**
     * 影响因素7-偏差值-名称
     */
    private String fac7Name;
    /**
     * 影响因素7-偏差值-值
     */
    private String fac7Value;
    /**
     * 影响因素7-偏差值-单位
     */
    private String fac7Unit;

    /**
     * 影响因素8-偏差值-名称
     */
    private String fac8Name;
    /**
     * 影响因素8-偏差值-值
     */
    private String fac8Value;
    /**
     * 影响因素8-偏差值-单位
     */
    private String fac8Unit;

    /**
     * 影响因素9-偏差值-名称
     */
    private String fac9Name;
    /**
     * 影响因素9-偏差值-值
     */
    private String fac9Value;
    /**
     * 影响因素9-偏差值-单位
     */
    private String fac9Unit;

    /**
     * 影响因素10-偏差值-名称
     */
    private String fac10Name;
    /**
     * 影响因素10-偏差值-值
     */
    private String fac10Value;
    /**
     * 影响因素10-偏差值-单位
     */
    private String fac10Unit;

    /**
     * 影响因素11-偏差值-名称
     */
    private String fac11Name;
    /**
     * 影响因素11-偏差值-值
     */
    private String fac11Value;
    /**
     * 影响因素11-偏差值-单位
     */
    private String fac11Unit;

    /**
     * 影响因素12-偏差值-名称
     */
    private String fac12Name;
    /**
     * 影响因素12-偏差值-值
     */
    private String fac12Value;
    /**
     * 影响因素12-偏差值-单位
     */
    private String fac12Unit;

    /**
     * 影响因素13-偏差值-名称
     */
    private String fac13Name;
    /**
     * 影响因素13-偏差值-值
     */
    private String fac13Value;
    /**
     * 影响因素13-偏差值-单位
     */
    private String fac13Unit;

    /**
     * 影响因素14-偏差值-名称
     */
    private String fac14Name;
    /**
     * 影响因素14-偏差值-值
     */
    private String fac14Value;
    /**
     * 影响因素14-偏差值-单位
     */
    private String fac14Unit;

    /**
     * 影响因素15-偏差值-名称
     */
    private String fac15Name;
    /**
     * 影响因素15-偏差值-值
     */
    private String fac15Value;
    /**
     * 影响因素15-偏差值-单位
     */
    private String fac15Unit;

    /**
     * 影响因素16-偏差值-名称
     */
    private String fac16Name;
    /**
     * 影响因素16-偏差值-值
     */
    private String fac16Value;
    /**
     * 影响因素16-偏差值-单位
     */
    private String fac16Unit;

    /**
     * 影响因素17-偏差值-名称
     */
    private String fac17Name;
    /**
     * 影响因素17-偏差值-值
     */
    private String fac17Value;
    /**
     * 影响因素17-偏差值-单位
     */
    private String fac17Unit;

    /**
     * 影响因素18-偏差值-名称
     */
    private String fac18Name;
    /**
     * 影响因素18-偏差值-值
     */
    private String fac18Value;
    /**
     * 影响因素18-偏差值-单位
     */
    private String fac18Unit;

    /**
     * 影响因素19-偏差值-名称
     */
    private String fac19Name;
    /**
     * 影响因素19-偏差值-值
     */
    private String fac19Value;
    /**
     * 影响因素19-偏差值-单位
     */
    private String fac19Unit;

    /**
     * 影响因素20-偏差值-名称
     */
    private String fac20Name;
    /**
     * 影响因素20-偏差值-值
     */
    private String fac20Value;
    /**
     * 影响因素20-偏差值-单位
     */
    private String fac20Unit;

    /**
     * 创建时间

 ansteel-biz/src/main/java/com/iailab/module/ansteel/coking/service/CokingTraceDeviationService.java

@@ -18,5 +18,5 @@

    void save(List<CokingTraceDeviationEntity> entityList);

    void saveTraceDeviation(String relId, String process, String clock, JSONObject result, String chartcode, String row, String sugObj);
    void saveTraceDeviation(String relId, String process, String clock, String jsonString, String sugObj);
}

 ansteel-biz/src/main/java/com/iailab/module/ansteel/coking/service/impl/CokingTraceDeviationServiceImpl.java

@@ -1,5 +1,6 @@
package com.iailab.module.ansteel.coking.service.impl;

import cn.hutool.core.bean.BeanUtil;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONArray;
import com.alibaba.fastjson.JSONObject;
@@ -15,9 +16,7 @@
import org.springframework.util.CollectionUtils;

import java.math.BigDecimal;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.*;
import java.util.stream.Collectors;

/**
@@ -52,63 +51,54 @@
    }

    @Override
    public void saveTraceDeviation(String relId, String process, String clock, JSONObject result, String chartcode, String row, String sugObj) {
        List<ChartParamDTO> list = mcsApi.getChartParamList(chartcode);
        Map<String, String> indexMaps = list.stream().collect(Collectors.toMap(ChartParamDTO::getParamCode, e -> e.getParamName()));

        List<String> rowKeys = new ArrayList<>();
        result.forEach((key, value) -> {
            if (StringUtils.isNotBlank(key) && key.contains(row)) {
                rowKeys.add(key);
            }

        });
    public void saveTraceDeviation(String relId, String process, String clock, String jsonString, String sugObj) {
        JSONArray jsonArray = JSON.parseArray(jsonString);

        List<CokingTraceDeviationEntity> entityList = new ArrayList<>();
        for (String key : rowKeys) {
            JSONArray rowArr = JSON.parseArray(result.get(key).toString());
            if (CollectionUtils.isEmpty(rowArr)) {
                continue;
        for (int i = 0; i < jsonArray.size(); i++) {
            JSONObject jsonObject = jsonArray.getJSONObject(i);

            Map<String,String> values = new HashMap<>();
            // 指标
            for (int index = 1; index <= 2; index++) {
                String indexKey = "index" + index;
                if (jsonObject.containsKey(indexKey)) {
                    String nameValue = jsonObject.getString(indexKey);
                    if (StringUtils.isBlank(nameValue)) {
                        continue;
                    }
                    String[] split = nameValue.split(" ");
                    String name = split[0];
                    String value = split[1];

                    values.put("ind" + index + "Name",name);
                    values.put("ind" + index + "Value",value);
                }
            }
            // 影响因素
            for (int index = 1; index <= 20; index++) {
                String factorKey = "factor" + index;
                if (jsonObject.containsKey(factorKey)) {
                    String nameValue = jsonObject.getString(factorKey);
                    if (StringUtils.isBlank(nameValue)) {
                        continue;
                    }
                    String[] split = nameValue.split(" ");
                    String name = split[0];
                    String value = split[1];

                    values.put("fac" + index + "Name",name);
                    values.put("fac" + index + "Value",value);
                }
            }

            CokingTraceDeviationEntity entity = new CokingTraceDeviationEntity();
            BeanUtil.fillBeanWithMap(values,entity,true);
            entity.setRelId(relId);
            entity.setProcess(process);
            entity.setClock(clock);
            entity.setSugObj(sugObj);

            entity.setInd1Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(0).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
            entity.setInd1Value(rowArr.getJSONArray(0).get(1).toString());
            entity.setInd1Unit("");

            entity.setInd2Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(1).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
            entity.setInd2Value(rowArr.getJSONArray(1).get(1).toString());
            entity.setInd2Unit("");

            if (rowArr.size() > 2) {
                entity.setFac1Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(2).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
                entity.setFac1Value(rowArr.getJSONArray(2).get(1).toString());
                entity.setFac1Unit("");
            }
            if (rowArr.size() > 3) {
                entity.setFac2Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(3).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
                entity.setFac2Value(rowArr.getJSONArray(3).get(1).toString());
                entity.setFac2Unit("");
            }
            if (rowArr.size() > 4) {
                entity.setFac3Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(4).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
                entity.setFac3Value(rowArr.getJSONArray(4).get(1).toString());
                entity.setFac3Unit("");
            }
            if (rowArr.size() > 5) {
                entity.setFac4Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(5).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
                entity.setFac4Value(rowArr.getJSONArray(5).get(1).toString());
                entity.setFac4Unit("");
            }
            if (rowArr.size() > 6) {
                entity.setFac5Name(indexMaps.get(new BigDecimal(rowArr.getJSONArray(6).get(0).toString()).setScale(0, BigDecimal.ROUND_HALF_UP).toString()));
                entity.setFac5Value(rowArr.getJSONArray(6).get(1).toString());
                entity.setFac5Unit("");
            }
            entity.setCreateDate(new Date());
            entityList.add(entity);
        }
        cokingTraceDeviationDao.insert(entityList);

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

@@ -10,6 +10,9 @@
import com.iailab.module.ansteel.common.enums.TraceProcessTypeEnum;
import com.iailab.module.model.api.mcs.McsApi;
import com.iailab.module.model.api.mdk.MdkApi;
import com.iailab.module.model.api.mdk.dto.MdkScheduleReqDTO;
import com.iailab.module.model.api.mdk.dto.MdkScheduleRespDTO;
import com.iailab.module.model.api.mdk.dto.StScheduleRecordVO;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
@@ -66,24 +69,9 @@

    private final static String indType = "备煤工序异常溯源";

    private final static String row = "coalRow";

    private final static String total = "coalPrepElecTotal1";

    private static final String jsonStr = "{\n" + "    " +
            "\"result\": {\n" +
            "\"coalHomeIndexInfo\":\"备煤耗电偏高\"," +
            "\"coalPrepElec\":[1600.8,1613.5]," +
            "\"coalPrepElecTotal1\":\"备煤耗电量偏高，经模型计算，原因和调整建议如下：煤量异常，当前值2000, 建议调整煤量至区间[765.0,1020.0]\"," +
            "\"coalPrepElecTime\":[[0.3,0.3],[1700.31,1900.2],[120.3]]," +
            "\"coalPrepElecIndex\":[133527.2,283517.6,83451.5,233461.2,83564.4]," +
            "\"coalRow0\":[[0.0,1000.3],[1.0,120.2],[7.0,1150.32]]," +
            "\"coalRow1\":[[0.0,1000.5],[2.0,200.56],[7.0,120.2]]," +
            "\"coalRow2\":[[0.0,1000.6],[3.0,261.7],[7.0,170.52]]," +
            "\"coalPrepElecHomePage\":[503000.6,84.04]," +
            "\"coalHomeIndex\":[30.0,4.6,523000.6]" +
            "  }" +
            "}";
    private String scheduleCode = "";
    private final String finalResultStrKey = "finalResultStr";
    private final String resultListKey = "resultList";

    @Override
    public void run(String params) {
@@ -104,20 +92,20 @@
            calendar.add(Calendar.MINUTE, -3);
            Date collectStartDate = 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;
@@ -125,18 +113,19 @@

            // 保存报告
            String analyDate = DateUtils.format(startDate);
            String analyContent = clock + " " + result.getString("coalHomeIndexInfo");
            String content = result.getString(total);
            String analyContent = "备煤异常";
            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);

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

@@ -8,13 +8,16 @@
import com.iailab.module.ansteel.common.enums.TraceProcessTypeEnum;
import com.iailab.module.model.api.mcs.McsApi;
import com.iailab.module.model.api.mdk.MdkApi;
import com.iailab.module.model.api.mdk.dto.StScheduleRecordVO;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import org.springframework.util.CollectionUtils;

import java.util.Calendar;
import java.util.Date;
import java.util.List;
import java.util.Objects;

/**
@@ -56,30 +59,15 @@

    private final static String indType = "干熄焦工序异常溯源";

    private final static String row = "steamRow";

    private final static String total = "steamTotal1";

    private final static String SugObj = "GXJ";

    private String scheduleCode = "AnSteelCDQTrackImplv3"; //焦化干熄焦产蒸汽模型
    private final String finalResultStrKey = "finalResultStr";
    private final String resultListKey = "resultList";

    @Autowired
    private CokingTraceChartService cokingTraceChartService;

    private static final String jsonStr = "{\"result\":{" +
            " \"steamProd\":[[0.76,0.76],[07,0.72],[0.74,0.68]]," +
            "\"steamRow0\":[[14.0,20.7],[14.0,30.5],[14.0,35.2],[24.0,67.9],[6.0,12.3]]," +
            "\"steamRow1\":[[10.0,5.5],[11.0,15.1],[21.0,20.6],[22.0,31.3],[8.0,42.5]]," +
            "\"steamRow2\":[[74.0,8.2],[36.0,18.2],[35.0,34.6],[9.0,62.4],[18.0,34.7]]," +
            "\"steamPressure\":[3.7,3.6,3.4]," +
            "\"steamHomePage\":[[220.4,223.5],[0.5],[673214.3]]," +
            "\"steamHomeIndexInfo\":\"干熄焦产蒸汽量异常\"," +
            "\"steamTemperature\":[461.3,460.4,456.6]," +
            "\"steamElec\":[233564.3,224571.7,246120.2,603157.7]," +
            "\"steamIndex\":[[3.182,3.265,3.275],[1250.3,1293.1,1264.05],[890.3,886.32,901.21],[161495.2,171043.5,168533.6],[203667.2,238742.6,226731.7],[223548.3,223097.9,226733.3]]," +
            "\"steamTotal1\":\"2#干熄焦蒸汽发生量因空气导入量偏高、锅炉入口温度偏低而减少13t，经模型计算，建议调整空气导入量，预计可使主蒸汽流量指标升高20m3/h\"," +
            "\"steamHomeIndex\":[[63.2,61.7],[62.8,67.2],[66.1,65.7],[204.6,220.5]]" +
            " }" +
            "}";

    @Override
    public void run(String params) {
@@ -100,19 +88,20 @@
            calendar.add(Calendar.MINUTE, -3);
            Date collectStartDate = 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 +109,19 @@

            // 保存报告
            String analyDate = DateUtils.format(startDate);
            String analyContent = clock + " " + result.getString("steamHomeIndexInfo");
            String content = result.getString(total);
            String analyContent = "干熄焦异常";
            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);

 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);

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

@@ -6,14 +6,18 @@
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.MdkApi;
import com.iailab.module.model.api.mdk.dto.StScheduleRecordVO;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import org.springframework.util.CollectionUtils;

import java.util.Calendar;
import java.util.Date;
import java.util.List;
import java.util.Objects;

/**
@@ -46,7 +50,7 @@
    private CokingTraceChartService cokingTraceChartService;

    @Autowired
    private MdkApi mdkApi;
    private McsApi mcsApi;

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

@@ -56,27 +60,9 @@

    private final static String indType = "炼焦工序异常溯源";

    private final static String row = "cokeRow";

    private final static String total = "cokeTotal";

    private static final String jsonStr = "{\n" +
            "\"result\": {\n" +
            "\"cokeElec\":[583562.4]," +
            "\"cokeHeat1\":[130820.4,136710.3]," +
            "\"cokeRow0\":[[0.0,13.6],[2.0,10.5],[69.0,34.6]]," +
            "\"cokeIndex\":[[0.0149,0.0148],[23.6,24.5],[1350.2,1423.5],[1.21,1.25],[0.28],[103542.3,135238.5],[104668.63,137826.5],[155678.2]]," +
            "\"cokeRow1\":[[0.0,12.51],[81.0,34.3],[69.0,42.3],[86.0,56.4],[92.0,89.4]]," +
            "\"cokeRow2\":[[0.0,45.3],[9.0,42.5],[81.0,31.2],[88.0,16.3]]," +
            "\"cokeHeat2\":[135220.3,134720.3]," +
            "\"cokeCOG2\":[64525.8,64824.2]," +
            "\"cokeHomeIndex\":[[90.4,90.2],[80.3,78.5],[103.6,100.3],[280.9,270.4]]," +
            "\"cokeHomeIndexInfo\":\"吨焦耗热量异常\"," +
            "\"cokeCOG1\":[64435.5,64532.6]," +
            "\"cokeHomePage\":[[124439.4,124428.4],[320.6],[224.3],[248305.4],[124436.2],[3.96],[0.43]]," +
            "\"cokeTotal\":\"炼焦吨焦耗热量因煤气流量偏高、煤气水分偏低而增加23，经模型计算，延建议调整煤气流量，预计可使吨焦耗热量指标降低17\"" +
            " }" +
            "}";
    private String scheduleCode = "lianjiaoguankong"; //焦化炼焦管控模型
    private final String finalResultStrKey = "finalResultStr";
    private final String resultListKey = "resultList";

    @Override
    public void run(String params) {
@@ -97,20 +83,20 @@
            calendar.add(Calendar.MINUTE, -3);
            Date collectStartDate = 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;
@@ -118,18 +104,19 @@

            // 保存报告
            String analyDate = DateUtils.format(startDate);
            String analyContent = clock + " " + result.getString("cokeHomeIndexInfo");
            String content = result.getString(total);
            String analyContent = "炼焦异常";
            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);

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

@@ -22,17 +22,11 @@
    private Logger logger = LoggerFactory.getLogger(getClass());

    private String AnStellCOAL = "AnStellCOAL"; //焦化备煤管控
    private String AnSteelCDQTrackImplv3 = "AnSteelCDQTrackImplv3"; //焦化干熄焦产蒸汽模型
    private String AnSteelChemProSteamTrack = "AnSteelChemProSteamTrack"; //焦化化产蒸汽消耗模型
    private String lianjiaoguankong = "lianjiaoguankong"; //焦化炼焦管控模型

    @Autowired
    private MdkApi mdkApi;
    @Autowired
    private McsApi mcsApi;

    private final String finalResultStrKey = "finalResultStr";
    private final String resultListKey = "resultList";


    @Override
@@ -77,78 +71,6 @@
                    suggestDto.setTitle("焦化备煤建议");
                    suggestDto.setContent(equipOperationInfo.toString());
                    suggestDto.setScheduleObj("COAL");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);
                }
            }
            //焦化干熄焦产蒸汽模型 建议保存
            if (AnSteelCDQTrackImplv3.equals(code)) {
                Object finalResultStr =  mdkScheduleRespDTO.getResult().get(finalResultStrKey);
                if(finalResultStr != null && StringUtils.isNotBlank(finalResultStr.toString())) {
                    ScheduleSuggestRespDTO suggestDto = new ScheduleSuggestRespDTO();
                    suggestDto.setTitle("干熄焦产蒸汽建议");
                    suggestDto.setContent(finalResultStr.toString());
                    suggestDto.setScheduleObj("GXJCZQ");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);
                }

                Object resultList =  mdkScheduleRespDTO.getResult().get(resultListKey);
                if(resultList != null && StringUtils.isNotBlank(resultList.toString())) {
                    ScheduleSuggestRespDTO suggestDto = new ScheduleSuggestRespDTO();
                    suggestDto.setTitle("干熄焦产蒸汽异常溯源");
                    suggestDto.setContent(resultList.toString());
                    suggestDto.setScheduleObj("GXJCZQ_YCSY");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);
                }
            }
            //焦化化产蒸汽消耗模型 建议保存
            if (AnSteelChemProSteamTrack.equals(code)) {
                Object finalResultStr =  mdkScheduleRespDTO.getResult().get(finalResultStrKey);
                if(finalResultStr != null && StringUtils.isNotBlank(finalResultStr.toString())) {
                    ScheduleSuggestRespDTO suggestDto = new ScheduleSuggestRespDTO();
                    suggestDto.setTitle("化产蒸汽消耗建议");
                    suggestDto.setContent(finalResultStr.toString());
                    suggestDto.setScheduleObj("HCZQXH");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);
                }

                Object resultList =  mdkScheduleRespDTO.getResult().get(resultListKey);
                if(resultList != null && StringUtils.isNotBlank(resultList.toString())) {
                    ScheduleSuggestRespDTO suggestDto = new ScheduleSuggestRespDTO();
                    suggestDto.setTitle("化产蒸汽消耗异常溯源");
                    suggestDto.setContent(resultList.toString());
                    suggestDto.setScheduleObj("HCZQXH_YCSY");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);
                }
            }
            //焦化炼焦管控模型 建议保存
            if (lianjiaoguankong.equals(code)) {
                Object finalResultStr =  mdkScheduleRespDTO.getResult().get(finalResultStrKey);
                if(finalResultStr != null && StringUtils.isNotBlank(finalResultStr.toString())) {
                    ScheduleSuggestRespDTO suggestDto = new ScheduleSuggestRespDTO();
                    suggestDto.setTitle("炼焦管控建议");
                    suggestDto.setContent(finalResultStr.toString());
                    suggestDto.setScheduleObj("LJGK");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);
                }

                Object resultList =  mdkScheduleRespDTO.getResult().get(resultListKey);
                if(resultList != null && StringUtils.isNotBlank(resultList.toString())) {
                    ScheduleSuggestRespDTO suggestDto = new ScheduleSuggestRespDTO();
                    suggestDto.setTitle("炼焦管控异常溯源");
                    suggestDto.setContent(resultList.toString());
                    suggestDto.setScheduleObj("LJGK_YCSY");
                    suggestDto.setScheduleTime(dto.getScheduleTime());
                    suggestDto.setCreateTime(new Date());
                    mcsApi.createScheduleSuggest(suggestDto);

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

@@ -83,13 +83,13 @@
                JSONArray jsonArr = JSON.parseArray(substationMap.get("reason").toString());
                for(int i=0; i<jsonArr.size(); i++){
                    Object element = jsonArr.get(i);
                    content = content + JSON.toJSONString(element) + ";";
                    content = content + JSON.toJSONString(element).replace("\"","") + ";";
                }

                AlarmMessageRespDTO alarmMessageRespDTO = new AlarmMessageRespDTO();
                alarmMessageRespDTO.setTitle(substationMap.get("66kVOverLimit").toString());
                alarmMessageRespDTO.setContent(content);
                alarmMessageRespDTO.setAlarmObj(ALARM_OBJ);
                alarmMessageRespDTO.setAlarmObj("FactorAlarm");
                alarmMessageRespDTO.setAlarmTime(mdkScheduleRespDTO.getScheduleTime());
                alarmMessageRespDTO.setCreateTime(calendar.getTime());


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

@@ -1,13 +1,26 @@
package com.iailab.module.ansteel.job.task;

import cn.hutool.core.bean.BeanUtil;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONArray;
import com.alibaba.fastjson.JSONObject;
import com.iailab.module.ansteel.common.constant.CommonConstant;
import com.iailab.module.model.api.mcs.McsApi;
import com.iailab.module.model.api.mcs.dto.AlarmMessageRespDTO;
import com.iailab.module.model.api.mdk.MdkApi;
import com.iailab.module.model.api.mdk.dto.MdkScheduleReqDTO;
import com.iailab.module.model.api.mdk.dto.MdkScheduleRespDTO;
import org.apache.commons.lang3.StringUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import org.springframework.util.CollectionUtils;

import java.util.ArrayList;
import java.util.Calendar;
import java.util.List;
import java.util.Map;

/**
 * @author PanZhibao
@@ -23,26 +36,66 @@
    @Autowired
    private McsApi mcsApi;

    @Autowired
    private MdkApi mdkApi;
    @Override
    public void run(String params) {
//        {'status_code': 100, 'result': {
//        'code220': '100', 'code66': '100',
//        '220kVPointReactivePowerInjectionIntoGrid': {'title': '220KV望铁关口无功上网', 'reason': '["大型发电机无功增加", "热轧甲线: 无功减少可能由工序检修引起"]'},
//        '66kVPointReactivePowerInjectionIntoGrid': {'title': '66KV范家变无功上网', 'reason': '["范铁乙线无功上网：可能因工序突降导致无功减少", "范钢甲线无功上网：炼钢总降#2电容器投运, 炼钢总降#4电容器投运, 炼钢总降#6电容器投运, 炼钢总降#8电容器投运", "范氧甲线无功上网"]'}}}
        logger.info("RunPowerNetAlarmTask定时任务正在执行，参数为：{}", params);
        try {
            Calendar calendar = Calendar.getInstance();
            calendar.set(Calendar.SECOND, 0);
            calendar.set(Calendar.MILLISECOND, 0);

            AlarmMessageRespDTO alarmMessageRespDTO = new AlarmMessageRespDTO();
            alarmMessageRespDTO.setContent("焦化甲线: 无功减少可能由该工序下电容器投运引起;原料甲线: 可能由工序检修引起; 1#炼铁线: 无功减少可能由1#TRT发电机无功增加引起; 2#氧气线: 可能由工序检修引起");
            alarmMessageRespDTO.setTitle("大型发电机无功增加");
            alarmMessageRespDTO.setAlarmObj(ALARM_OBJ);
            alarmMessageRespDTO.setAlarmTime(calendar.getTime());
            alarmMessageRespDTO.setCreateTime(calendar.getTime());

            mcsApi.createAlarmMessage(alarmMessageRespDTO);
            MdkScheduleReqDTO dto = new MdkScheduleReqDTO();
            dto.setScheduleTime(calendar.getTime());
            dto.setScheduleCode(ALARM_OBJ);
            MdkScheduleRespDTO mdkScheduleRespDTO = mdkApi.doSchedule(dto);
            logger.info(params + "调度方案执行完成，" + mdkScheduleRespDTO);
            if(!CommonConstant.MDK_STATUS_100.equals(mdkScheduleRespDTO.getStatusCode())){
                logger.info(params + "运行异常");
                return;
            }
            JSONObject obj = new JSONObject(mdkScheduleRespDTO.getResult());
            Map<String,Object> result = BeanUtil.beanToMap(obj);
            if(CommonConstant.MDK_STATUS_100.equals(result.get("code220"))){
                createAlarmMessage(result,"220kVPointReactivePowerInjectionIntoGrid",calendar);
            }
            if(CommonConstant.MDK_STATUS_100.equals(result.get("code66"))){
                createAlarmMessage(result,"66kVPointReactivePowerInjectionIntoGrid",calendar);
            }
        } catch (Exception ex) {
            logger.error("RunPowerNetAlarmTask运行异常");
            ex.printStackTrace();
        }
        logger.info("RunPowerNetAlarmTask运行完成");
    }
    private void createAlarmMessage( Map<String,Object> result , String type,Calendar calendar){
        Map<String,Object> map = BeanUtil.beanToMap(result.get(type));
        if (CollectionUtils.isEmpty(map) || map.get("reason") == null) {
            return;
        }
        try {
            StringBuilder contentBuilder = new StringBuilder();
            JSONArray jsonArr = JSON.parseArray(map.get("reason").toString());
            for(int i = 0; i < jsonArr.size(); i++) {
                Object element = jsonArr.get(i);
                if (element != null) {
                    contentBuilder.append(JSON.toJSONString(element).replace("\"","")).append(";");
                }
            }

            AlarmMessageRespDTO alarmMessageRespDTO = new AlarmMessageRespDTO();
            alarmMessageRespDTO.setContent(contentBuilder.toString());
            alarmMessageRespDTO.setTitle(map.get("title").toString());
            alarmMessageRespDTO.setAlarmObj("NetAlarm");
            alarmMessageRespDTO.setAlarmTime(calendar.getTime());
            alarmMessageRespDTO.setCreateTime(calendar.getTime());
            mcsApi.createAlarmMessage(alarmMessageRespDTO);
        } catch (Exception e) {
            logger.error("创建报警消息失败", e);
        }
    }
}

 doc/鞍钢数据接口文档_master.doc

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