data_analyze_platform/LIB/FRONTEND/FaultDetection/main_pred.py

from LIB.MIDDLE.FaultDetection.V1_0_2.aelstm import *
import pymysql
import datetime
import pandas as pd
from LIB.BACKEND import DBManager
dbManager = DBManager.DBManager()
from sqlalchemy import create_engine
from urllib import parse
import datetime, time
from apscheduler.schedulers.blocking import BlockingScheduler
import traceback
import pickle
from keras.models import load_model
import logging
import logging.handlers
import os
import re


#...................................故障检测函数......................................................................................................................
def diag_cal():
    global SNnums
    global scaler_dict, scaler2_dict, model_dict, model2_dict

    start=time.time()
    now_time=datetime.datetime.now()
    start_time=now_time-datetime.timedelta(hours=3)
    start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
    end_time=now_time.strftime('%Y-%m-%d %H:%M:%S')

    #数据库配置
    host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
    port=3306
    db='safety_platform'
    user='qx_read'
    password='Qx@123456'

    #读取结果库数据......................................................
    param='product_id,start_time,end_time,diff_min,SOC,AnoScoreV_sum_max,AnoScoreV_max_max,AnoScoreT_sum_max,AnoScoreT_max_max'
    tablename='fault_detection'
    mysql = pymysql.connect (host=host, user=user, password=password, port=port, database=db)
    cursor = mysql.cursor()
    sql =  "select {} from {} where end_time='0000-00-00 00:00:00'".format(param,tablename)
    cursor.execute(sql)
    res = cursor.fetchall()
    df_diag_ram= pd.DataFrame(res,columns=param.split(','))
    

    db_res_engine = create_engine(
        "mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8".format(
            user, parse.quote_plus(password), host, port, db
        ))


    #调用主函数................................................................................................................................................................
    for sn in SNnums:
        try:
            group=sn[:5]
            df_data = dbManager.get_data(sn=sn, start_time=start_time, end_time=end_time, data_groups=['bms'])
            data_bms = df_data['bms']
            data_bms['sn']=sn
            if len(data_bms)>0:
                logger.info("SN: {} 数据开始预处理".format(sn))
                data_stand=data_groups(data_bms,sn,start_time,end_time)
                df_stand=split(data_stand)   
                res=pd.DataFrame()
                if len(df_stand)>0:
                    #读取训练产出的缩放指标：均值&方差
                    logger.info("SN: {} 数据开始模型预测".format(sn))
                    scaler = scaler_dict[group]
                    scaler2 = scaler2_dict[group]
                    #读取训练产出的模型状态空间：电压模型&温度模型
                    model = model_dict[group]
                    model2 = model2_dict[group]
                    res=prediction(df_stand,scaler,scaler2,model,model2)
                    if len(res)>0:
                        df_res2,diff=threshold(res,group,end_time)
                        df_diag_ram_sn=df_diag_ram[df_diag_ram['product_id']==sn]
                        if not df_diag_ram_sn.empty:   #该sn相关结果非空
                            new_res,update_res=arrange(df_res2,df_diag_ram_sn,start_time,diff)
                            if len(update_res)>0:
                                cursor.execute("DELETE FROM fault_detection WHERE end_time = '0000-00-00 00:00:00' and product_id='{}'".format(sn))
                                mysql.commit()
                                update_res.to_sql("fault_detection",con=db_res_engine, if_exists="append",index=False)
                            #新增结果存入结果库................................................................
                            if len(new_res)>0:
                                new_res.to_sql("fault_detection",con=db_res_engine, if_exists="append",index=False)
                        else:
                            df_res2.to_sql("fault_detection",con=db_res_engine, if_exists="append",index=False)

            # end=time.time()
            # print(end-start)  
                
        except Exception as e:
            logger.error(str(e))
            logger.error(traceback.format_exc())

    cursor.close()
    mysql.close()

#...............................................主函数起定时作用.......................................................................................................................
if __name__ == "__main__":
    
    # 日志
    log_path = 'log/'
    if not os.path.exists(log_path):
        os.makedirs(log_path)
    logger = logging.getLogger("main")
    logger.setLevel(logging.DEBUG)
    
     # 根据日期滚动(每天产生1个文件)
    fh = logging.handlers.TimedRotatingFileHandler(filename='{}/main_info.log'.format(log_path), when="D", interval=1, backupCount=30,
                                                    encoding="utf-8")
    formatter = logging.Formatter("%(asctime)s - %(name)s-%(levelname)s %(message)s")
    fh.suffix = "%Y-%m-%d_%H-%M-%S"
    fh.extMatch = re.compile(r"^\d{4}-\d{2}-\d{2}_\d{2}-\d{2}-\d{2}")
    fh.setFormatter(formatter)
    fh.setLevel(logging.INFO)
    logger.addHandler(fh)

    fh = logging.handlers.TimedRotatingFileHandler(filename='{}/main_error.log'.format(log_path), when="D", interval=1, backupCount=30,
                                                    encoding="utf-8")
    formatter = logging.Formatter("%(asctime)s - %(name)s-%(levelname)s %(message)s")
    fh.suffix = "%Y-%m-%d_%H-%M-%S"
    fh.extMatch = re.compile(r"^\d{4}-\d{2}-\d{2}_\d{2}-\d{2}-\d{2}")
    fh.setFormatter(formatter)
    fh.setLevel(logging.ERROR)
    logger.addHandler(fh)

    logger.info("pid is {}".format(os.getpid()))
    
     # # 更新sn列表
    host='rm-bp10j10qy42bzy0q7.mysql.rds.aliyuncs.com'
    port=3306
    db='qixiang_oss'
    user='qixiang_oss'
    password='Qixiang2021'
    conn = pymysql.connect(host=host, port=port, user=user, password=password, database=db)
    cursor = conn.cursor()
    cursor.execute("select sn, imei, add_time from app_device where status in (1,2,3)")
    res = cursor.fetchall()
    df_sn = pd.DataFrame(res, columns=['sn', 'imei', 'add_time'])
    df_sn = df_sn.reset_index(drop=True)
    conn.close();
    
    SNnums = list(df_sn['sn'])
    
    scaler_list=[]
    scaler2_list=[]
    model_list=[]
    model2_list=[]
    for group in ['MGMLX','PK504','PK502','PK500','MGMCL']:
        scaler = pickle.load(open('D:/deploy/python_platform/data_analyze_platform/LIB/MIDDLE/FaultDetection/V1_0_2/train_out/scalerV_'+group+'_10.pkl', 'rb'))
        scaler2 = pickle.load(open('D:/deploy/python_platform/data_analyze_platform/LIB/MIDDLE/FaultDetection/V1_0_2/train_out/scalerT_'+group+'_10.pkl', 'rb'))
        model = load_model('D:/deploy/python_platform/data_analyze_platform/LIB/MIDDLE/FaultDetection/V1_0_2/train_out/modelV_'+group+'_10.h5')
        model2 = load_model('D:/deploy/python_platform/data_analyze_platform/LIB/MIDDLE/FaultDetection/V1_0_2/train_out/modelT_'+group+'_10.h5')
        scaler_list.append(scaler)
        scaler2_list.append(scaler2)
        model_list.append(model)
        model2_list.append(model2)
    scaler_dict={'MGMLX':scaler_list[0],'PK504':scaler_list[1],'PK502':scaler_list[2],'PK500':scaler_list[3],'MGMCL':scaler_list[4]}
    scaler2_dict={'MGMLX':scaler2_list[0],'PK504':scaler2_list[1],'PK502':scaler2_list[2],'PK500':scaler2_list[3],'MGMCL':scaler2_list[4]}
    model_dict={'MGMLX':model_list[0],'PK504':model_list[1],'PK502':model_list[2],'PK500':model_list[3],'MGMCL':model_list[4]}
    model2_dict={'MGMLX':model2_list[0],'PK504':model2_list[1],'PK502':model2_list[2],'PK500':model2_list[3],'MGMCL':model2_list[4]}
    logger.info("模型加载完成")

    diag_cal()
    #定时任务.......................................................................................................................................................................
    scheduler = BlockingScheduler()
    scheduler.add_job(diag_cal, 'interval', hours=3)

    try:  
        scheduler.start()
    except Exception as e:
        scheduler.shutdown()
        logger.error(str(e))
        logger.error(traceback.format_exc())