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- import CBMSSafetyAlarm
- import datetime
- import pandas as pd
- import multiprocessing
- from LIB.BACKEND import DBManager, Log
- import time, datetime
- from apscheduler.schedulers.blocking import BlockingScheduler
- from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import log
- #...................................电池包电芯安全诊断函数......................................................................................................................
- def diag_cal(sn_list, df_diag_ram, df_bms_ram):
-
- start=time.time()
- now_time=datetime.datetime.now()
- start_time=now_time-datetime.timedelta(seconds=70)
- start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
- end_time=now_time.strftime('%Y-%m-%d %H:%M:%S')
- for sn in sn_list:
- 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']
- # print(df_bms)
- #电池诊断................................................................................................................................................................
- if not df_bms.empty:
- df_diag_ram_sn=df_diag_ram[df_diag_ram['product_id']==sn]
- df_bms_ram_sn=df_bms_ram[df_bms_ram['sn']==sn]
- if df_diag_ram_sn.empty:
- SafetyAlarm=CBMSSafetyAlarm.SafetyAlarm(sn,celltype,df_bms, df_bms_ram_sn)
- df_diag_res, df_bms_res=SafetyAlarm.diag()
- #更新bms的ram数据 和 diag的Ram数据
- sn_index=df_bms_ram.loc[df_bms_ram['sn']==sn].index
- df_bms_ram=df_bms_ram.drop(index=sn_index)
- df_bms_ram=df_bms_ram.append(df_bms_res)
- sn_index=df_diag_ram.loc[df_diag_ram['product_id']==sn].index
- df_diag_ram=df_diag_ram.drop(index=sn_index)
- df_diag_ram=df_diag_ram.append(df_diag_res)
- df_diag_ram.reset_index(inplace=True,drop=True) #重置索引
- #当前热失控故障写入数据库
- if not df_diag_res.empty:
- with open(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\06BatSafetyAlarm\热失控.txt','a') as file:
- file.write(str(tuple(df_diag_res.iloc[-1]))+'\n')
-
- #当前热失控已超过三天变为历史故障并写入数据库,并删除原有数据库中的当前故障和ram中的当前故障
- elif (now_time-df_bms_ram_sn.iloc[-1]['time']).total_seconds()>3*24*3600:
- df_diag_ram=df_diag_ram.drop(df_diag_ram['sn']==sn) #删除ram中的当前故障
- df_bms_ram_sn.iloc[-1]['end_time']=now_time
- with open(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\06BatSafetyAlarm\热失控.txt','a') as file:
- file.write(str(tuple(df_diag_res.iloc[-1]))+'\n')
- #故障处理........................................................................................................................................................
- end=time.time()
- print(end-start)
- # print(df_soh)
- #...................................................主进程...........................................................................................................
- def mainprocess():
- global SNnums
- global df_diag_ram
- global df_bms_ram
- process = 2
- pool = multiprocessing.Pool(processes = process)
- for i in range(process):
- sn_list = SNnums[i]
- pool.apply_async(diag_cal, (sn_list,df_diag_ram,df_bms_ram))
- pool.close()
- pool.join()
- #...............................................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=['PK50201A000002201']
-
- mylog=log.Mylog('log_diag.txt','error')
- mylog.logcfg()
- #............................模块运行前,先读取数据库中所有结束时间为0的数据,需要从数据库中读取...................................
- result=pd.read_excel(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\06BatSafetyAlarm\result.xlsx')
- df_diag_ram=result[(result['end_time']=='0000-00-00 00:00:00') & (result['code']==119)]
- df_bms_ram=pd.DataFrame(columns=['time', 'sn', 'packvolt', 'cellvolt', 'celltemp'])
- #定时任务.......................................................................................................................................................................
- scheduler = BlockingScheduler()
- scheduler.add_job(mainprocess, 'interval', seconds=60, id='diag_job')
- try:
- scheduler.start()
- except Exception as e:
- scheduler.shutdown()
- print(repr(e))
- mylog.logopt(e)
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