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- import CBMSBatDiag
- import pymysql
- import datetime
- import pandas as pd
- from LIB.BACKEND import DBManager
- import datetime
- from apscheduler.schedulers.blocking import BlockingScheduler
- from USER.SPF.alibaba.Common import DBDownload
- from USER.SPF.alibaba.Common import log
- #...................................电池包电芯安全诊断函数......................................................................................................................
- def diag_cal():
- global SNnums
- now_time=datetime.datetime.now()
- start_time=now_time-datetime.timedelta(seconds=65)
- 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='qx_cas'
- user='qx_read'
- password='Qx@123456'
- #读取故障结果库中当前故障......................................................
- param='time_st,time_sp,sn,faultcode,faultlv,faultinfo,faultadvice'
- tablename=''
- mysql = pymysql.connect (host=host, user=user, password=password, port=port, database=db)
- cursor = mysql.cursor()
- sql = "select %s from %s where time_sp='0000-00-00 00:00:00'" %(param,tablename)
- cursor.execute(sql)
- res = cursor.fetchall()
- df_diag_ram= pd.DataFram(res,columns=param.split(','))
- cursor.close()
- mysql.close()
- for sn in SNnums:
- if 'PK500' in sn:
- celltype=1 #6040三元电芯
- elif 'PK502' in sn:
- celltype=2 #4840三元电芯
- elif 'K504B' in sn:
- celltype=99 #60ah林磷酸铁锂电芯
- elif 'MGMLXN750' in sn:
- celltype=3 #力信50ah三元电芯
- elif 'MGMCLN750' or 'UD' in sn:
- celltype=4 #CATL 50ah三元电芯
- else:
- print('SN:{},未找到对应电池类型!!!'.format(sn))
- continue
- # sys.exit()
- #读取原始数据库数据........................................................................................................................................................
- dbManager = DBManager.DBManager()
- df_data = dbManager.get_data(sn=sn, start_time=start_time, end_time=end_time, data_groups=['bms'])
- df_bms = df_data['bms']
- #读取结果数据库数据........................................................................................................................................................
- mode=1
- tablename1='cellstateestimation_soh'
- tablename2='cellstateestimation_uniform_socvoltdiff'
- tablename3='cellstateestimation_soc'
- DBRead=DBDownload.DBDownload(host, port, db, user, password,mode)
- with DBRead as DBRead:
- df_soh=DBRead.getdata('time_st,sn,soh,cellsoh', tablename=tablename1, sn=sn, timename='time_sp', st=start_time, sp=end_time)
- df_uniform=DBRead.getdata('time,sn,cellsoc_diff,cellmin_num,cellmax_num', tablename=tablename2, sn=sn, timename='time', st=start_time, sp=end_time)
- df_soc=DBRead.getdata('time','sn','packsoc', tablename=tablename3, sn=sn)
- #电池诊断................................................................................................................................................................
- if not df_bms.empty:
- df_diag_ram_sn=df_diag_ram[df_diag_ram['sn']==sn]
- df_diag_ram_sn.reset_index(inplace=True,drop=True)
- batdiag=CBMSBatDiag.BatDiag(sn,celltype,df_bms,df_soh,df_soc,df_uniform,df_diag_ram_sn)
- df_diag_res, df_health_res=batdiag.diag() #获取电池故障结果和电池评分结果
- #电池评分写入数据库
- if not df_health_res.empty: #变为历史故障更改数据库
- with open(r'D:\00WorkSpace\01Python\data_analyze_platform\USER\alibaba\05BatDiag\电池评分.txt','a') as file:
- file.write(str(tuple(df_health_res))+'\n')
- #历史故障筛选并更改数据库故障结束时间.........................................................
- if not df_diag_res.empty:
- df_diag_now=df_diag_res[df_diag_res['time_sp'] == '0000-00-00 00:00:00'] #去除历史故障
- df_diag_new = pd.concat([df_diag_res,df_diag_ram_sn,df_diag_ram_sn]).drop_duplicates(subset=['time_st','faultcode'],keep=False)#此次判断中新增故障
- df_diag_end=pd.concat([df_diag_res,df_diag_new,df_diag_new]).drop_duplicates(subset=['time_st','faultcode'],keep=False)#此次判断中新增故障
- df_diag_end=df_diag_end[df_diag_end['time_sp'] != '0000-00-00 00:00:00']
- df_diag_end.reset_index(inplace=True,drop=True) #重置索引
- if not df_diag_end.empty: #变为历史故障更改数据库
- with open(r'D:\00WorkSpace\01Python\data_analyze_platform\USER\alibaba\05BatDiag\故障报警.txt','a') as file:
- file.write(str(tuple(df_diag_end))+'\n')
- #新增故障筛选并存入数据库.....................................................................
- if not df_diag_new.empty: #新增写入数据库
- with open(r'D:\00WorkSpace\01Python\data_analyze_platform\USER\alibaba\05BatDiag\故障报警.txt','a') as file:
- file.write(str(tuple(df_diag_new))+'\n')
- #更新diag的Ram数据
- df_diag_ram=df_diag_ram.drop(df_diag_ram[df_diag_ram.sn==sn].index)
- df_diag_ram=df_diag_ram.append(df_diag_now, ignore_index=True)
- df_diag_ram.reset_index(inplace=True,drop=True) #重置索引
- #健康度评分存入数据库
- #...............................................主函数起定时作用.......................................................................................................................
- if __name__ == "__main__":
-
- excelpath=r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\sn-20210903.xlsx'
- SNdata_6060 = pd.read_excel(excelpath, sheet_name='科易6060')
- SNdata_6040 = pd.read_excel(excelpath, sheet_name='科易6040')
- SNdata_4840 = pd.read_excel(excelpath, sheet_name='科易4840')
- SNdata_L7255 = pd.read_excel(excelpath, sheet_name='格林美-力信7255')
- SNdata_C7255 = pd.read_excel(excelpath, sheet_name='格林美-CATL7255')
- SNdata_U7255 = pd.read_excel(excelpath, sheet_name='优旦7255')
- SNnums_6060=SNdata_6060['SN号'].tolist()
- SNnums_6040=SNdata_6040['SN号'].tolist()
- SNnums_4840=SNdata_4840['SN号'].tolist()
- SNnums_L7255=SNdata_L7255['SN号'].tolist()
- SNnums_C7255=SNdata_C7255['SN号'].tolist()
- SNnums_U7255=SNdata_U7255['SN号'].tolist()
- SNnums=SNnums_L7255 + SNnums_C7255 + SNnums_U7255, SNnums_6040 + SNnums_4840 + SNnums_6060
- SNnums=['HUATING']
-
- mylog=log.Mylog('log_diag.txt','error')
- mylog.logcfg()
- #定时任务.......................................................................................................................................................................
- scheduler = BlockingScheduler()
- scheduler.add_job(diag_cal, 'interval', seconds=60)
- try:
- scheduler.start()
- except Exception as e:
- scheduler.shutdown()
- print(repr(e))
- mylog.logopt(e)
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