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- import sys
- import numpy as np
- import pandas as pd
- import string
- import os
- from pandas import Series
- from matplotlib import pyplot as plt
- from pandas.core.frame import DataFrame
- from pandas.core.indexes.base import Index
- from LIB.BACKEND import DBManager
- import datetime
- import time
- import string
- import re
- class SamplingSafty:
- def __init__(self):
- pass
- def main(sn,param,bms_info,df_Diag_Ram_in):
- df_Diag_Ram_Update_inside=DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice'])
- df_Diag_Ram_Update_inside=df_Diag_Ram_Update_inside.append(df_Diag_Ram_in)
- global QuitErrCount
- VolStarkCount=[0 for i in range(param.CellVoltNums)]
- VolCount=0
- QuitErrCount=[0 for i in range(param.FaultCount)]
- #--------------该电池的所有当前故障-------------
- for i in range(0,len(bms_info)):
- if i==0:
- bms_infoP=bms_info.loc[i]
- elif len(bms_info)>=1:
- bms_infoP=bms_info.loc[i-1]
- df_Diag_Ram_Update_inside,VolStarkCount,VolCount=SamplingSafty.VoltSamplingDiag(sn,bms_info.loc[i],bms_infoP,param,VolStarkCount,VolCount,df_Diag_Ram_Update_inside)
- df_Diag_Ram_Update_inside=SamplingSafty.TempSamplingDiag(sn,bms_info.loc[i],bms_infoP,param,df_Diag_Ram_Update_inside)
- # FltInfo=SamplingSafty.CrntSamplingDiag(sn,bms_info.loc[i],FltInfo,param)
- return df_Diag_Ram_Update_inside
- def VoltSamplingDiag(sn,bms_infoN,bms_infoP,param,VolStarkCount,VolCount,df_Diag_Ram):
- InVMaxBatNo=[]
- InVMinBatNo=[]
- StackVolNo=[]
- OutlierVolNo=[]
- ErrorFlg=0
- #——————————————————————取最高最低电压————————————————————————————————
- VoltageNum=['单体电压'+str(i) for i in range(1,param.CellVoltNums+1)]
- CellVoltage=bms_infoN[VoltageNum]/1000
- CellVoltageP=bms_infoP[VoltageNum]/1000
- MaxVolt=CellVoltage.max()
- MinVolt=CellVoltage.min()
- MaxVoltNum=CellVoltage[MaxVolt==CellVoltage].index
- MinVoltNum=CellVoltage[MinVolt==CellVoltage].index
- InVMaxBatNo=CellVoltage[CellVoltage>=param.CellOVlmt].index
- InVMinBatNo=CellVoltage[CellVoltage<=param.CellUVlmt].index
- if param.CellVoltNums>2:
- AvgVol=(CellVoltage.sum()-MaxVolt-MinVolt)/(param.CellVoltNums-2)
- else:
- AvgVol=CellVoltage.mean()
- #—————————————————————————————电压无效和断线判断———————————————————————
- if len(InVMaxBatNo):
- if len(InVMinBatNo):
- QuitErrCount[10]=0
- if not 10 in df_Diag_Ram['code'].values.tolist():#如果故障发生当前故障中没有该故障,则压入该故障
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,10,2,'电池电压采样断线,最高电压为{:.2f}V,电池编号为{},最低电压为{:.2f}V,电池编号为{}'.format(MaxVolt,InVMaxBatNo.values,MinVolt,InVMinBatNo.values),'返厂维修']
- ErrorFlg=1
- else:#如果故障发生当前故障中有该故障,则不进行操作
- pass
- else:#如果没有故障,并且当前故障表中有该故障,则判断故障是否结束
- QuitErrCount[50]=0
- if 10 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[10]=QuitErrCount[10]+1
- if QuitErrCount[10]>3:
- QuitErrCount[10]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==10].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- if not 50 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,50,2,str(InVMaxBatNo.values)+'号电压大于{:.2f}V,采样无效'.format(param.CellOVlmt),'返厂维修']
- ErrorFlg=1
- else:
- pass
- elif len(InVMinBatNo):
- QuitErrCount[50]=0
- if not 50 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,50,2,str(InVMinBatNo.values)+'号电压小于{:.2f}V,采样无效'.format(param.CellUVlmt),'返厂维修']
- ErrorFlg=1
- else:
- pass
- else:
- if 50 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[50]=QuitErrCount[50]+1
- if QuitErrCount[50]>3:
- QuitErrCount[50]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==50].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- #——————————————————————————————————电压卡滞和离群判断—————————————————————————
- if ErrorFlg==0:
- AvgVolGap=CellVoltage-AvgVol
- OutlierVolNo=AvgVolGap[AvgVolGap>=param.AvgVolGap].index
- if len(OutlierVolNo) and abs(bms_infoN['总电流[A]'])<2 and not 51 in df_Diag_Ram['code']:
- VolCount=VolCount+1
- QuitErrCount[51]=0
- if VolCount>10:
- VolCount=11
- if not 51 in df_Diag_Ram['code'].values.tolist():#如果故障发生当前故障中没有该故障,则压入该故障
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,51,2,str(OutlierVolNo.values)+'号电池电压离群','技术介入诊断']
- ErrorFlg=1
- else:#如果故障发生当前故障中有该故障,则不进行操作
- pass
- else:
- VolCount=0
- if 51 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[51]=QuitErrCount[51]+1
- if QuitErrCount[51]>3:
- QuitErrCount[51]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==51].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- # -------------------卡滞逻辑未加-------------------------------------
- # if (abs(float(bms_infoN['总电流[A]']))>=10 and not 'PK504' in sn) or (abs(float(bms_infoN['总电流[A]']))>=15 and 'PK504' in sn):
- # StackVolNo=CellVoltage[abs(CellVoltage-CellVoltageP)<=0.0001].index
- # NotStackVolNo=CellVoltage[abs(CellVoltage-CellVoltageP)>0.0001].index
- # if len(StackVolNo) and not 52 in df_Diag_Ram['code']:
- # StackVolNo=[int(s) for s in StackVolNo.str.replace(r'[^0-9]','').tolist()]
- # NotStackVolNo=[int(s) for s in NotStackVolNo.str.replace(r'[^0-9]','').tolist()]
- # for i in StackVolNo:
- # VolStarkCount[i-1]=VolStarkCount[i-1]+1
- # for i in NotStackVolNo:
- # VolStarkCount[i-1]=0
- # if [s for s in VolStarkCount]>10:
- # StacVolNo=
- return df_Diag_Ram,VolStarkCount,VolCount
- def TempSamplingDiag(sn,bms_infoN,bms_infoP,param,df_Diag_Ram):
- InVMaxBatNo=[]
- InVMinBatNo=[]
- StackVolNo=[]
- OutlierVolNo=[]
- ErrorFlg=0
- #——————————————————————Cell取最高最低温度————————————————————————————————
- TempNum=['单体温度'+str(i) for i in range(1,param.CellTempNums+1)]
- CellTemp=bms_infoN[TempNum]
- CellTempP=bms_infoP[TempNum]
- maxCellTemp=CellTemp.max()
- minCellTemp=CellTemp.min()
- MaxVoltNum=CellTemp[maxCellTemp==CellTemp].index
- MinVoltNum=CellTemp[minCellTemp==CellTemp].index
- InVMaxTempBatNo=CellTemp[CellTemp>=param.PackOTlmt].index
- InVMinTempBatNo=CellTemp[CellTemp<=param.PackUTlmt].index
- if param.CellTempNums>2:
- AvgCellTemp=(CellTemp.sum()-maxCellTemp-minCellTemp)/(param.CellTempNums-2)
- else:
- AvgCellTemp=CellTemp.mean()
- #——————————————————————温度无效,离群和断线判断———————————————————————
- if len(InVMaxTempBatNo):
- if len(InVMinTempBatNo):
- QuitErrCount[53]=0
- if not 53 in df_Diag_Ram['code'].values.tolist():#如果故障发生当前故障中没有该故障,则压入该故障
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,53,2,'电池温度采样断线,最高温度为{}℃,电池编号为{},最低温度为{}℃,电池编号为{}'.format(maxCellTemp,InVMaxTempBatNo.values,minCellTemp,InVMinTempBatNo.values),'返厂维修']
- ErrorFlg=1
- else:#如果故障发生当前故障中有该故障,则不进行操作
- pass
- else:#如果没有故障,并且当前故障表中有该故障,则判断故障是否结束
- QuitErrCount[2]=0
- if 53 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[53]=QuitErrCount[53]+1
- if QuitErrCount[53]>3:
- QuitErrCount[53]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==53].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- if not 2 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,2,2,str(InVMaxTempBatNo.values)+'号温度大于{}℃,采样无效'.format(param.PackOTlmt),'联系用户核实电池温度情况,并返厂维修']
- ErrorFlg=1
- else:
- pass
- elif len(InVMinTempBatNo):
- QuitErrCount[2]=0
- if not 2 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,2,2,str(InVMinTempBatNo.values)+'号温度小于{}℃,采样无效'.format(param.PackUTlmt),'返厂维修']
- ErrorFlg=1
- else:
- pass
- else:
- if 2 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[2]=QuitErrCount[2]+1
- if QuitErrCount[2]>3:
- QuitErrCount[2]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==2].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- if ErrorFlg==0:
- AvgCellTempGap=abs(CellTemp-AvgCellTemp)
- OutlierTempNo=AvgCellTempGap[AvgCellTempGap>=param.AvgCellTempGap].index
- if len(OutlierTempNo):
- QuitErrCount[8]=0
- if not 8 in df_Diag_Ram['code'].values.tolist():#如果故障发生当前故障中没有该故障,则压入该故障
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,8,2,str(OutlierTempNo.values)+'号电池异常温度离群','技术介入诊断']
- ErrorFlg=1
- else:#如果故障发生当前故障中有该故障,则不进行操作
- pass
- else:
- if 8 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[8]=QuitErrCount[8]+1
- if QuitErrCount[8]>3:
- QuitErrCount[8]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==8].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- #——————————————————————————————————OtherTemp————————————————————————————————————
- if param.OtherTempNums>0:
- OtherTempNum=['其他温度'+str(i) for i in range(1,param.OtherTempNums+1)]
- OtherTemp=bms_infoN[OtherTempNum]
- if 'MGMLX' in sn:
- OtherTemp['其他温度2']=OtherTemp['其他温度1']
- else:
- pass
- OtherTemppP=bms_infoP[OtherTempNum]
- maxOtherTemp=OtherTemp.max()
- minOtherTemp=OtherTemp.min()
- MaxVoltNum=OtherTemp[maxOtherTemp==OtherTemp].index
- MinVoltNum=OtherTemp[minOtherTemp==OtherTemp].index
- InVMaxOtherTempBatNo=OtherTemp[OtherTemp>=param.OtherOTlmt].index
- InVMinOtherTempBatNo=OtherTemp[OtherTemp<=param.OtherUTlmt].index
- if param.OtherTempNums>2:
- AvgOtherTemp=(OtherTemp.sum()-maxOtherTemp-minOtherTemp)/(param.OtherTempNums-2)
- else:
- AvgOtherTemp=OtherTemp.mean()
- #——————————————————————温度无效,离群和断线判断———————————————————————
- if len(InVMaxOtherTempBatNo):
- if len(InVMinOtherTempBatNo):
- QuitErrCount[54]=0
- if not 54 in df_Diag_Ram['code'].values.tolist():#如果故障发生当前故障中没有该故障,则压入该故障
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,54,2,'其他温度采样断线,最高温度为{}℃,传感器编号为{},最低温度为{}℃,传感器编号为{}'.format(maxOtherTemp,InVMaxOtherTempBatNo.values,minOtherTemp,InVMinOtherTempBatNo.values),'返厂维修']
- ErrorFlg=1
- else:#如果故障发生当前故障中有该故障,则不进行操作
- pass
- else:#如果没有故障,并且当前故障表中有该故障,则判断故障是否结束
- QuitErrCount[55]=0
- if 54 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[54]=QuitErrCount[54]+1
- if QuitErrCount[54]>3:
- QuitErrCount[54]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==54].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- if not 55 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,55,2,'传感器温度大于{}℃,采样无效'.format(param.OtherOTlmt),'联系用户核实电池温度情况,并返厂维修']
- ErrorFlg=1
- else:
- pass
- elif len(InVMinTempBatNo):
- QuitErrCount[55]=0
- if not 55 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,55,2,'传感器温度小于{}℃,采样无效'.format(param.OtherUTlmt),'返厂维修']
- ErrorFlg=1
- else:
- pass
- else:
- if 55 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[55]=QuitErrCount[55]+1
- if QuitErrCount[55]>3:
- QuitErrCount[55]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==55].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- if ErrorFlg==0:
- AvgOtherTempGap=abs(OtherTemp-AvgOtherTemp)
- OutlierOtherTempNo=AvgOtherTempGap[AvgOtherTempGap>=param.AvgOtherTempGap].index
- if len(OutlierOtherTempNo):
- QuitErrCount[56]=0
- if not 56 in df_Diag_Ram['code'].values.tolist():#如果故障发生当前故障中没有该故障,则压入该故障
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,56,2,'传感器温度异常离群','技术介入诊断']
- ErrorFlg=1
- else:#如果故障发生当前故障中有该故障,则不进行操作
- pass
- else:
- if 56 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[56]=QuitErrCount[56]+1
- if QuitErrCount[56]>3:
- QuitErrCount[56]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==56].index,['end_time']]=end_time
- else:
- pass
- else:
- pass
- if (maxOtherTemp-maxCellTemp)>param.AvgOtherTempGap and maxOtherTemp<param.OtherOTlmt and maxCellTemp<param.PackOTlmt:
- QuitErrCount[56]=0
- if not 56 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,56,2,'传感器温度异常离群','技术立即介入诊断']
- ErrorFlg=1
- else:
- if 56 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[56]=QuitErrCount[56]+1
- if QuitErrCount[56]>3:
- QuitErrCount[56]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==56].index,['end_time']]=end_time
-
- if (maxCellTemp-maxOtherTemp)>param.AvgOtherTempGap and maxOtherTemp<param.OtherOTlmt and maxCellTemp<param.PackOTlmt and not 8 in df_Diag_Ram['code']:
- QuitErrCount[8]=0
- if not 8 in df_Diag_Ram['code'].values.tolist():
- df_Diag_Ram.loc[len(df_Diag_Ram)]=[bms_infoN['时间戳'],'0000-00-00 00:00:00',sn,8,2,str(OutlierTempNo.values)+'号电芯温度异常离群','技术立即介入诊断']
-
- ErrorFlg=1
- else:
- if 8 in df_Diag_Ram['code'].values.tolist():
- QuitErrCount[8]=QuitErrCount[8]+1
- if QuitErrCount[8]>3:
- QuitErrCount[8]=4
- end_time=datetime.datetime.now()
- end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
- df_Diag_Ram.loc[df_Diag_Ram[df_Diag_Ram['code']==8].index,['end_time']]=end_time
- return df_Diag_Ram
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