data_analyze_platform/LIB/MIDDLE/SaftyCenter/Liplated/main.py

import datetime
import pandas as pd
from LIB.BACKEND import DBManager, Log
import time, datetime
from apscheduler.schedulers.blocking import BlockingScheduler
import log
from pandas.core.frame import DataFrame
import Li_plated
import vol_sor_est
from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import BatParam

#...................................电池包电芯安全诊断函数......................................................................................................................
def cell_platd_sorvol_test():
    global SNnums
    global df_Diag_lipltd
    global df_diag_sor
    global df_diag_vol
    global df_diag_volsor
    start=time.time()
    now_time=datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
    now_time=datetime.datetime.strptime(now_time,'%Y-%m-%d %H:%M:%S')
    start_time=now_time-datetime.timedelta(days=3)
    end_time=str(now_time)
    start_time=str(start_time)
    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........................................................................................................................................................
        start_time = '2021-11-23 12:00:00'
        end_time = '2021-11-24 12:00:00'
        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']
        df_Diag_lipltd_add = pd.DataFrame(columns = ['sn','time','liplated', 'liplated_amount'])

        #析锂诊断................................................................................................................................................................
        if not df_bms.empty:
            Diag_lipltd_temp = Li_plated.Liplated_test(sn,celltype,df_bms)#析锂检测
            df_Diag_lipltd_add = Diag_lipltd_temp.liplated_detect()
            # Diag_sorvol_temp = vol_sor_est.vol_sor_est(sn,celltype,df_bms)#电压内阻估计
            # [df_diag_sor_add, df_diag_vol_add, df_diag_sorvol_add] = Diag_sorvol_temp.volsor_cal()           
        if not df_Diag_lipltd_add.empty:
            df_Diag_lipltd_temp = df_Diag_lipltd.append(df_Diag_lipltd_add)
            df_Diag_lipltd = df_Diag_lipltd_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
            df_Diag_lipltd.reset_index(drop = True)
            df_Diag_lipltd.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
            df_Diag_lipltd.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\02析锂检测\01下载数据\格林美-力信7255\SNnums_6040_liplated_sn.csv',index=False,encoding='GB18030')
        # if not df_diag_sor_add.empty:
        #     df_diag_sor_temp = df_diag_sor.append(df_diag_sor_add)
        #     df_diag_sor = df_diag_sor_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
        #     df_diag_sor.reset_index(drop = True)
        #     df_diag_sor.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
        #     df_diag_sor.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\内阻偏离.csv',index=False,encoding='GB18030')
        # if not df_diag_vol_add.empty:
        #     df_diag_vol_temp = df_diag_vol.append(df_diag_vol_add)
        #     df_diag_vol = df_diag_vol_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
        #     df_diag_vol.reset_index(drop = True)
        #     df_diag_vol.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
        #     df_diag_vol.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\电压偏离.csv',index=False,encoding='GB18030')
        # if not df_diag_sorvol_add.empty:
        #     df_diag_volsor_temp = df_diag_volsor.append(df_diag_sorvol_add)
        #     df_diag_volsor = df_diag_volsor_temp.drop_duplicates(subset = ['sn','time'], keep = 'first', inplace = False)
        #     df_diag_volsor.reset_index(drop = True)
        #     df_diag_volsor.sort_values(by = ['sn'], axis = 0, ascending=True,inplace=True)#对故障信息按照时间进行排序
        #     df_diag_volsor.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\电压内阻偏离.csv',index=False,encoding='GB18030')
        end=time.time()
        print(end-start)

#...............................................主函数.......................................................................................................................
if __name__ == "__main__":
    global SNnums
    global df_Diag_lipltd
    global df_diag_sor
    global df_diag_vol
    global df_diag_volsor
    
    excelpath=r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\04故障诊断\01Screen_Problem\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_6040 + SNnums_4840 + SNnums_U7255+ SNnums_6060
    SNnums=['MGMCLN750N215N296','MGMCLN750N215N080', 'MGMCLN750N215I108', 'MGMCLN750N215N217']
    # SNnums = SNnums_6040 #SNnums_C7255 #SNnums_6040['MGMCLN750N215N049'] 
    # SNnums = pd.read_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\02析锂检测\liplated\疑似析锂电池sn.csv',encoding='GB18030')
    
    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................
    df_Diag_lipltd=pd.read_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\02析锂检测\01下载数据\格林美-力信7255\析锂.csv',encoding='GB18030')
    # df_diag_sor = pd.read_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\内阻偏离.csv',encoding='GB18030')
    # df_diag_vol = pd.read_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\电压偏离.csv',encoding='GB18030')
    # df_diag_volsor = pd.read_csv(r'D:\Work\Code_write\data_analyze_platform\USER\lzx\01算法开发\05内阻及电压估计\02算法检测\判断结果\电压内阻偏离.csv',encoding='GB18030')

    print('-------计算中-----------')
    #定时任务.......................................................................................................................................................................
    scheduler = BlockingScheduler()
    scheduler.add_job(cell_platd_sorvol_test, 'interval', seconds=10, id='diag_job')
    

    try:  
        scheduler.start()
    except Exception as e:
        scheduler.shutdown()
        print(repr(e))
        mylog.logopt(e)