data_analyze_platform/USER/SPF/01qixiang/03BatInterShort/CBMSBatInterShort.py

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# from pymysql import paramstyle
from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import BatParam

class BatInterShort():
    def __init__(self,sn,celltype,df_bms,df_soh):  #参数初始化

        self.sn=sn
        self.celltype=celltype
        self.param=BatParam.BatParam(celltype)
        self.df_bms=df_bms
        self.packcrnt=df_bms['总电流[A]']*self.param.PackCrntDec
        self.packvolt=df_bms['总电压[V]']
        self.bms_soc=df_bms['SOC[%]']
        self.bmstime= pd.to_datetime(df_bms['时间戳'], format='%Y-%m-%d %H:%M:%S')

        self.df_soh=df_soh

        self.cellvolt_name=['单体电压'+str(x) for x in range(1,self.param.CellVoltNums+1)]
        self.celltemp_name=['单体温度'+str(x) for x in range(1,self.param.CellTempNums+1)]
    
    def intershort(self):
        if self.celltype<50:
            df_res=self._ncm_intershort()
            return df_res
            
        elif self.celltype>50:
            df_res=self._lfp_intershort()
            return df_res
        
        else:
            return pd.DataFrame()

    #定义滑动滤波函数....................................................................................
    def _np_move_avg(self,a, n, mode="same"): 
        return (np.convolve(a, np.ones((n,)) / n, mode=mode))
    
    #寻找当前行数据的最小温度值.............................................................................
    def _celltemp_weight(self,num):   
        celltemp = list(self.df_bms.loc[num,self.celltemp_name])
        celltemp=np.mean(celltemp)
        self.celltemp=celltemp
        if self.celltype==99:
            if celltemp>=20:
                self.tempweight=1
                self.StandardStandingTime=3600
            elif celltemp>=10:
                self.tempweight=0.6
                self.StandardStandingTime=7200
            elif celltemp>=5:
                self.tempweight=0.
                self.StandardStandingTime=7200
            else:
                self.tempweight=0.1
                self.StandardStandingTime=10800
        else:
            if celltemp>=20:
                self.tempweight=1
                self.StandardStandingTime=3600
            elif celltemp>=10:
                self.tempweight=0.8
                self.StandardStandingTime=3600
            elif celltemp>=5:
                self.tempweight=0.6
                self.StandardStandingTime=7200
            else:
                self.tempweight=0.2
                self.StandardStandingTime=10800

    #获取当前行所有电压数据........................................................................................
    def _cellvolt_get(self,num): 
        cellvolt = np.array(self.df_bms.loc[num,self.cellvolt_name])/1000
        return cellvolt

    #获取当前行所有soc差...........................................................................................
    def _celldeltsoc_get(self,num,dict_baltime,capacity): 
        cellsoc=[]
        celldeltsoc=[]
        for j in range(1, self.param.CellVoltNums+1):   #获取每个电芯电压对应的SOC值
            cellvolt=self.df_bms.loc[num,'单体电压' + str(j)]/1000
            ocv_soc=np.interp(cellvolt,self.param.LookTab_OCV,self.param.LookTab_SOC)
            if j in dict_baltime.keys():
                ocv_soc=ocv_soc+dict_baltime[j]*self.param.BalCurrent/(capacity*3600)   #补偿均衡电流
            else:
                pass
            cellsoc.append(ocv_soc)
        
        if self.celltype==1 or self.celltype==2:
            consum_num=7
            cellsoc1=cellsoc[:self.param.CellVoltNums-consum_num]    #切片，将bms耗电的电芯和非耗电的电芯分离开
            cellsocmean1=(sum(cellsoc1)-max(cellsoc1)-min(cellsoc1))/(len(cellsoc1)-2)
            cellsoc2=cellsoc[self.param.CellVoltNums-consum_num:]
            cellsocmean2=(sum(cellsoc2)-max(cellsoc2)-min(cellsoc2))/(len(cellsoc2)-2)
            
            for j in range(len(cellsoc)):   #计算每个电芯的soc差
                if j<self.param.CellVoltNums-consum_num:
                    celldeltsoc.append(cellsoc[j]-cellsocmean1)
                else:
                    celldeltsoc.append(cellsoc[j]-cellsocmean2)
            return np.array(celldeltsoc)

        else:
            cellsocmean=(sum(cellsoc)-max(cellsoc)-min(cellsoc))/(len(cellsoc)-2)
            for j in range(len(cellsoc)):   #计算每个电芯的soc差
                celldeltsoc.append(cellsoc[j]-cellsocmean)
            return np.array(celldeltsoc)
 
    #获取所有电芯的As差
    def _cellDeltAs_get(self,chrg_st,chrg_end,dict_baltime):
        cellAs=[]
        celldeltAs=[]
        for j in range(1, self.param.CellVoltNums+1):   #获取每个电芯电压>峰值电压的充入As数
            if j in dict_baltime.keys():    #补偿均衡电流
                As=-self.param.BalCurrent*dict_baltime[j]
            else:    
                As=0
            As_tatol=0
            symbol=0
            for m in range(chrg_st+1,chrg_end):
                As=As-self.packcrnt[m]*(self.bmstime[m]-self.bmstime[m-1]).total_seconds()
                if symbol<5:
                    if self.df_bms.loc[m,'单体电压'+str(j)]/1000>self.param.PeakCellVolt[symbol]:
                        As_tatol=As_tatol+As
                        symbol=symbol+1
                    else:
                        continue
                else:
                    cellAs.append(As_tatol/5)
                    break
        
        if self.celltype==99:
            consum_num=10
            cellAs1=cellAs[:self.param.CellVoltNums-consum_num]    #切片，将bms耗电的电芯和非耗电的电芯分离开
            cellAsmean1=(sum(cellAs1)-max(cellAs1)-min(cellAs1))/(len(cellAs1)-2)
            cellAs2=cellAs[self.param.CellVoltNums-consum_num:]
            cellAsmean2=(sum(cellAs2)-max(cellAs2)-min(cellAs2))/(len(cellAs2)-2)
            
            for j in range(len(cellAs)):   #计算每个电芯的soc差
                if j<self.param.CellVoltNums-consum_num:
                    celldeltAs.append(cellAs[j]-cellAsmean1)
                else:
                    celldeltAs.append(cellAs[j]-cellAsmean2)
        else:
            cellAsmean=(sum(cellAs)-max(cellAs)-min(cellAs))/(len(cellAs)-2)
            for j in range(len(cellAs)):   #计算每个电芯的soc差
                celldeltAs.append(cellAs[j]-cellAsmean)
            
        return np.array(celldeltAs)

    #计算每个电芯的均衡时长..........................................................................................................................
    def _bal_time(self,dict_bal):
        dict_baltime={}
        dict_baltime1={}
        for key in dict_bal:
            count=1
            x=eval(key)
            while x>0:
                if x & 1==1:    #判断最后一位是否为1
                    if count in dict_baltime.keys():
                        dict_baltime[count] = dict_baltime[count] + dict_bal[key]
                    else:
                        dict_baltime[count] = dict_bal[key]
                else:
                    pass
                count += 1
                x >>= 1    #右移一位
        
        dict_baltime=dict(sorted(dict_baltime.items(),key=lambda dict_baltime:dict_baltime[0]))
        for key in dict_baltime:    #解析均衡的电芯编号
            if self.celltype==1:    #科易6040
                if key<14:
                    dict_baltime1[key]=dict_baltime[key]
                elif key<18:
                    dict_baltime1[key-1]=dict_baltime[key]
                else:
                    dict_baltime1[key-3]=dict_baltime[key]
            elif self.celltype==1:    #科易4840
                if key<4:
                    dict_baltime1[key-1]=dict_baltime[key]
                elif key<8:
                    dict_baltime1[key-1]=dict_baltime[key]
                elif key<14:
                    dict_baltime1[key-3]=dict_baltime[key]
                elif key<18:
                    dict_baltime1[key-4]=dict_baltime[key]
                else:
                    dict_baltime1[key-6]=dict_baltime[key]
            else:
                dict_baltime1=dict_baltime
        return dict_baltime1

    #三元电池的内短路电流计算...........................................................................................................................................................
    def _ncm_intershort(self):
        column_name=['time_st', 'time_sp', 'sn', 'method','short_current','baltime']
        df_res=pd.DataFrame(columns=column_name)
        
        if not self.df_bms.empty:
            if self.df_soh.empty:
                batsoh=self.df_bms.loc[0,'SOH[%]']
                capacity=self.param.Capacity*batsoh/100
            else:
                batsoh=self.df_soh.loc[len(self.df_soh)-1,'soh']
                capacity=self.param.Capacity*batsoh/100
            standingtime=0
            standingtime1=0
            firsttime=1
            firsttime1=1
            dict_bal={}
            dict_bal1={}

            for i in range(2,len(self.df_bms)-2):

                if firsttime1==0:   #满电静置算法--计算均衡状态对应的均衡时间
                    try:
                        balstat=int(self.df_bms.loc[i,'单体均衡状态'])
                        if balstat>0.5:
                            bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
                            bal_step=int(bal_step)
                            if str(balstat) in dict_bal1.keys():
                                dict_bal1[str(balstat)]=dict_bal1[str(balstat)]+bal_step
                            else:
                                dict_bal1[str(balstat)]=bal_step
                        else:
                            pass
                    except:
                        dict_bal1={}
                else:
                    pass

                if abs(self.packcrnt[i]) < 0.1 and abs(self.packcrnt[i-1]) < 0.1 and abs(self.packcrnt[i+1]) < 0.1:     
                    delttime=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                    standingtime=standingtime+delttime
                    standingtime1=standingtime1+delttime
                    self._celltemp_weight(i)

                    #静置法计算内短路-开始.....................................................................................................................................
                    if firsttime==1:    
                        if standingtime>self.StandardStandingTime*2:      #静置时间满足要求
                            standingtime=0
                            cellvolt_now=self._cellvolt_get(i)
                            cellvolt_min=min(cellvolt_now)
                            cellvolt_max=max(cellvolt_now)
                            cellvolt_last=self._cellvolt_get(i-1)
                            deltvolt=max(abs(cellvolt_now-cellvolt_last))

                            if 2<cellvolt_min<4.5 and 2<cellvolt_max<4.5 and deltvolt<0.005: 
                                dict_baltime=self._bal_time(dict_bal)   #获取每个电芯的均衡时间
                                deltsoc_last=self._celldeltsoc_get(i,dict_baltime,capacity)
                                time_last=self.bmstime[i]
                                firsttime=0
                        else:
                            pass                
                    elif standingtime>3600*10:
                        standingtime=0
                        cellvolt_now=self._cellvolt_get(i)
                        cellvolt_min=min(cellvolt_now)
                        cellvolt_max=max(cellvolt_now)
                        cellvolt_last=self._cellvolt_get(i-1)
                        deltvolt=max(abs(cellvolt_now-cellvolt_last))
                        
                        if 2<cellvolt_min<4.5 and 2<cellvolt_max<4.5 and deltvolt<0.005:
                            dict_baltime=self._bal_time(dict_bal)   #获取每个电芯的均衡时间
                            deltsoc_now=self._celldeltsoc_get(i,dict_baltime,capacity)
                            time_now=self.bmstime[i]
                            
                            list_sub=deltsoc_now-deltsoc_last
                            list_pud=0.01*capacity*3600*1000/(time_now-time_last).total_seconds()
                            leak_current=list_sub*list_pud
                            # leak_current=np.array(leak_current)
                            leak_current=np.round(leak_current,3)
                            leak_current=list(leak_current)
                            
                            df_res.loc[len(df_res)]=[time_last,time_now,self.sn,1,str(leak_current),str(dict_baltime)]  #计算结果存入Dataframe
                            time_last=time_now  #更新时间
                            deltsoc_last=deltsoc_now    #更新soc差
                            dict_bal={}
                    else: 
                        try:  
                            balstat=int(self.df_bms.loc[i,'单体均衡状态'])
                            if balstat>0.5:
                                bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
                                bal_step=int(bal_step)
                                if str(balstat) in dict_bal.keys():
                                    dict_bal[str(balstat)]=dict_bal[str(balstat)]+bal_step
                                else:
                                    dict_bal[str(balstat)]=bal_step
                            else:
                                pass
                        except:
                            dict_bal={}

                    #满电静置法计算内短路-开始.....................................................................................................................................................
                    if self.StandardStandingTime<standingtime1:  
                        standingtime1=0
                        cellvolt_now1=self._cellvolt_get(i)
                        cellvolt_max1=max(cellvolt_now1)
                        cellvolt_min1=min(cellvolt_now1)
                        cellvolt_last1=self._cellvolt_get(i-1)
                        deltvolt1=max(abs(cellvolt_now1-cellvolt_last1))
                        cellsoc_now1=np.interp(cellvolt_max1,self.param.LookTab_OCV,self.param.LookTab_SOC)

                        if cellsoc_now1>=self.param.FullChrgSoc-10 and 2<cellvolt_min1<4.5 and 2<cellvolt_max1<4.5 and deltvolt1<0.005:
                            if firsttime1==1:
                                dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
                                deltsoc_last1=self._celldeltsoc_get(i,dict_baltime1,capacity)
                                time_last1=self.bmstime[i]
                                firsttime1=0
                            else:
                                dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
                                time_now1=self.bmstime[i]
                                if (time_now1-time_last1).total_seconds()>3600*12:
                                    deltsoc_now1=self._celldeltsoc_get(i,dict_baltime1,capacity)

                                    list_sub1=deltsoc_now1-deltsoc_last1
                                    list_pud1=0.01*capacity*3600*1000/(time_now1-time_last1).total_seconds()
                                    leak_current1=list_sub1*list_pud1
                                    # leak_current1=np.array(leak_current1)
                                    leak_current1=np.round(leak_current1,3)
                                    leak_current1=list(leak_current1)
                                    
                                    df_res.loc[len(df_res)]=[time_last1,time_now1,self.sn,2,str(leak_current1),str(dict_baltime1)]  #计算结果存入Dataframe
                                    time_last1=time_now1  #更新时间
                                    deltsoc_last1=deltsoc_now1    #更新soc差
                                    dict_bal1={}
                                else:
                                    pass
                        else:
                            pass
                    else:   
                        pass

                else:
                    dict_bal={} 
                    firsttime=1
                    standingtime=0
                    standingtime1=0
                    pass

        if df_res.empty:    #返回计算结果
            return pd.DataFrame()
        else:
            return df_res

    #磷酸铁锂电池内短路计算程序.............................................................................................................................
    def _lfp_intershort(self):
        column_name=['time_st', 'time_sp', 'sn', 'method','short_current','baltime']
        df_res=pd.DataFrame(columns=column_name)
        if not self.df_bms.empty:
            if self.df_soh.empty:
                batsoh=self.df_bms.loc[0,'SOH[%]']
                capacity=self.param.Capacity*batsoh/100
            else:
                batsoh=self.df_soh.loc[len(self.df_soh)-1,'soh']
                capacity=self.param.Capacity*batsoh/100
            standingtime=0
            standingtime1=0
            firsttime=1
            firsttime1=1
            dict_bal={}
            dict_bal1={}

            chrg_start=[]
            chrg_end=[]
            dict_bal_list=[]
            charging=0
            dict_bal3={}

            for i in range(3,len(self.df_bms)-3):

                #静置法计算内短路..........................................................................................................................
                if firsttime1==0:   #满电静置算法--计算均衡状态对应的均衡时间
                    try:
                        balstat=int(self.df_bms.loc[i,'单体均衡状态'])
                        if balstat>0.5:
                            bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
                            bal_step=int(bal_step)
                            if str(balstat) in dict_bal1.keys():
                                dict_bal1[str(balstat)]=dict_bal1[str(balstat)]+bal_step
                            else:
                                dict_bal1[str(balstat)]=bal_step
                        else:
                            pass
                    except:
                        dict_bal1={}
                else:
                    pass

                if abs(self.packcrnt[i]) < 0.1 and abs(self.packcrnt[i-1]) < 0.1 and abs(self.packcrnt[i+1]) < 0.1:     
                    delttime=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                    standingtime=standingtime+delttime
                    standingtime1=standingtime1+delttime
                    self._celltemp_weight(i)

                    #静置法计算内短路-开始.....................................................................................................................................
                    if firsttime==1:    
                        if standingtime>self.StandardStandingTime:      #静置时间满足要求
                            standingtime=0
                            cellvolt_now=self._cellvolt_get(i)
                            cellvolt_min=min(cellvolt_now)
                            cellvolt_max=max(cellvolt_now)
                            cellvolt_last=self._cellvolt_get(i-1)
                            deltvolt=max(abs(cellvolt_now-cellvolt_last))

                            if 2<cellvolt_max<self.param.OcvInflexionBelow-0.002 and 2<cellvolt_min<4.5 and abs(deltvolt)<0.003:
                                dict_baltime=self._bal_time(dict_bal)   #获取每个电芯的均衡时间
                                deltsoc_last=self._celldeltsoc_get(i,dict_baltime,capacity)
                                time_last=self.bmstime[i]
                                firsttime=0
                            else:
                                pass
                        else:
                            pass                
                    elif standingtime>3600*12:
                        standingtime=0
                        cellvolt_now=np.array(self._cellvolt_get(i))
                        cellvolt_min=min(cellvolt_now)
                        cellvolt_max=max(cellvolt_now)
                        cellvolt_last=np.array(self._cellvolt_get(i-1))
                        deltvolt=max(abs(cellvolt_now-cellvolt_last))

                        if 2<cellvolt_max<self.param.OcvInflexionBelow-0.002 and 2<cellvolt_min<4.5  and abs(deltvolt)<0.003:
                            dict_baltime=self._bal_time(dict_bal)   #获取每个电芯的均衡时间
                            deltsoc_now=self._celldeltsoc_get(i, dict_baltime,capacity)    #获取每个电芯的SOC差
                            time_now=self.bmstime[i]

                            list_sub=deltsoc_now-deltsoc_last
                            list_pud=0.01*capacity*3600*1000/(time_now-time_last).total_seconds()
                            leak_current=list_sub*list_pud
                            # leak_current=np.array(leak_current)
                            leak_current=np.round(leak_current,3)
                            leak_current=list(leak_current)
                            
                            df_res.loc[len(df_res)]=[time_last,time_now,self.sn,1,str(leak_current),str(dict_baltime)]  #计算结果存入Dataframe
                            time_last=time_now  #更新时间
                            deltsoc_last=deltsoc_now    #更新soc差
                            dict_bal={}
                        else:
                            pass
                    else: 
                        try:  
                            balstat=int(self.df_bms.loc[i,'单体均衡状态'])
                            if balstat>0.5:
                                bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
                                bal_step=int(bal_step)
                                if str(balstat) in dict_bal.keys():
                                    dict_bal[str(balstat)]=dict_bal[str(balstat)]+bal_step
                                else:
                                    dict_bal[str(balstat)]=bal_step
                            else:
                                pass
                        except:
                            dict_bal={}

                    #非平台区间静置法计算内短路-开始.....................................................................................................................................................
                    if standingtime1>self.StandardStandingTime: 
                        if abs(self.packcrnt[i+2]) >= 0.1: 
                            standingtime1=0
                            cellvolt_now1=self._cellvolt_get(i)
                            cellvolt_max1=max(cellvolt_now1)
                            cellvolt_min1=min(cellvolt_now1)
                            cellvolt_last1=self._cellvolt_get(i-1)
                            deltvolt1=max(abs(cellvolt_now1-cellvolt_last1))
                        
                            if 2<cellvolt_max1<self.param.OcvInflexionBelow-0.002 and 2<cellvolt_min1<4.5 and deltvolt1<0.005:
                                if firsttime1==1:
                                    dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
                                    deltsoc_last1=self._celldeltsoc_get(i,dict_baltime1,capacity)
                                    time_last1=self.bmstime[i]
                                    firsttime1=0
                                else:
                                    dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
                                    deltsoc_now1=self._celldeltsoc_get(i,dict_baltime1,capacity)
                                    time_now1=self.bmstime[i]

                                    time_now1=self.bmstime[i]
                                    if abs(max(deltsoc_now1)-max(deltsoc_last1))<10 and (time_now1-time_last1).total_seconds()>3600*24:
                                        list_sub1=deltsoc_now1-deltsoc_last1
                                        list_pud1=0.01*capacity*3600*1000/(time_now1-time_last1).total_seconds()
                                        leak_current1=list_sub1*list_pud1
                                        # leak_current1=np.array(leak_current1)
                                        leak_current1=np.round(leak_current1,3)
                                        leak_current1=list(leak_current1)
                                        
                                        df_res.loc[len(df_res)]=[time_last1,time_now1,self.sn,2,str(leak_current1),str(dict_baltime1)]  #计算结果存入Dataframe
                                        time_last1=time_now1  #更新时间
                                        deltsoc_last1=deltsoc_now1    #更新soc差
                                        dict_bal1={}
                                    else:
                                        pass
                                    
                            else:
                                pass
                        else:
                            pass
                    else:   
                        pass

                else:
                    dict_bal={} 
                    firsttime=1
                    standingtime=0
                    standingtime1=0
                    pass

                #获取充电数据——开始..............................................................................................................
                try:
                    balstat=int(self.df_bms.loc[i,'单体均衡状态'])  #统计均衡状态
                    if balstat>0.5:
                        bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
                        bal_step=int(bal_step)
                        if str(balstat) in dict_bal3.keys():
                            dict_bal3[str(balstat)]=dict_bal3[str(balstat)]+bal_step
                        else:
                            dict_bal3[str(balstat)]=bal_step
                    else:
                        pass
                except:
                    dict_bal3={}

                if charging==0:
                    
                    if self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and self.packcrnt[i+2]<=-1 and self.bms_soc[i]<40:     #判断充电开始
                        cellvolt_now=self._cellvolt_get(i)
                        if min(cellvolt_now)<self.param.CellFullChrgVolt-0.15:
                            charging=1
                            if len(chrg_start)>len(chrg_end):
                                chrg_start[-1]=i
                            else:
                                chrg_start.append(i)
                        else:
                            pass
                    else:
                        pass

                else: #充电中
                    if (self.bmstime[i+1]-self.bmstime[i]).total_seconds()>180 or (self.packcrnt[i]>self.param.Capacity/3 and self.packcrnt[i+1]>self.param.Capacity/3):  #如果充电过程中时间间隔>180s，则舍弃该次充电
                        chrg_start.remove(chrg_start[-1])
                        charging=0
                        continue
                    elif self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and  self.packcrnt[i+2]<-1:  
                        cellvolt_now=self._cellvolt_get(i)
                        if min(cellvolt_now)>self.param.CellFullChrgVolt-0.13:   #电压>满充电压-0.13V，即3.37V
                            self._celltemp_weight(i)
                            if i-chrg_start[-1]>10 and self.celltemp>10:
                                chrg_end.append(i+1)
                                dict_bal_list.append(dict_bal3)
                                dict_bal3={}
                                charging=0                       
                                continue
                            else:
                                chrg_start.remove(chrg_start[-1])
                                charging=0
                                continue
                        else:
                            pass
                    else:
                        pass   
            
            #基于充电数据计算单体电芯的漏电流..........................................................................................................
            if len(chrg_end)>1:    
                for i in range(len(chrg_end)):
                    if i<1:
                        dict_baltime={}
                        deltAs_last=self._cellDeltAs_get(chrg_start[i],chrg_end[i],dict_baltime)
                        time_last=self.bmstime[chrg_end[i]]
                    else:
                        dict_baltime=self._bal_time(dict_bal_list[i])   #获取每个电芯的均衡时间
                        deltAs_now=self._cellDeltAs_get(chrg_start[i],chrg_end[i],dict_baltime)  #获取每个电芯的As差
                        time_now=self.bmstime[chrg_end[i]]

                        list_sub=deltAs_now-deltAs_last
                        list_pud=-1000/(time_now-time_last).total_seconds()
                        leak_current=list_sub*list_pud
                        # leak_current=np.array(leak_current)
                        leak_current=np.round(leak_current,3)
                        leak_current=list(leak_current)

                        df_res.loc[len(df_res)]=[time_last,time_now,self.sn,3,str(leak_current),str(dict_baltime)]  #计算结果存入Dataframe
                        deltAs_last=deltAs_now
                        time_last=time_now
            else:
                pass

        if df_res.empty:
            return pd.DataFrame()
        else:
            return df_res