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@@ -48,6 +48,8 @@ class SafetyWarning:
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mk_z_list=[]
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mk_Tau_list=[]
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mk_slope_list=[]
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+ mk_s_list=[]
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+ mk_svar_list=[]
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if not self.df_short.empty:
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short_current=self.df_short['short_current']
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@@ -87,8 +89,7 @@ class SafetyWarning:
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cellvolt_rank=self.df_uniform['cellvolt_rank']
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cellvolt_rank=cellvolt_rank.str.replace("[", '')
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cellvolt_rank=cellvolt_rank.str.replace("]", '')
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-
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- # plt.figure()
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+
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for i in range(self.param.CellVoltNums):
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#漏电流故障判断...........................................................................
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if not self.df_short.empty:
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@@ -114,14 +115,14 @@ class SafetyWarning:
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y=VoltChange[volt_column[i]]
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volt3sigma=np.array(Volt_3Sigma[volt_column[i]].map(lambda x:eval(x)))
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volt3sigma_sum=np.sum(volt3sigma<-3)
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- # #电压变化率
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- # a1,b1=np.polyfit(VoltChange['time'].tolist(),y.tolist(),1)
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- # y1=a1*VoltChange['time']+b1
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- # y_mean=y.mean()
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- # R2=1-(np.sum((y1-y)**2))/(np.sum((y-y_mean)**2))
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- # R2_list.append(R2)
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+ #电压变化率
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+ a1,b1=np.polyfit(VoltChange['time'].tolist(),y.tolist(),1)
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+ y1=a1*VoltChange['time']+b1
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+ y_mean=y.mean()
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+ R2=1-(np.sum((y1-y)**2))/(np.sum((y-y_mean)**2))
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+ R2_list.append(R2)
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- # volt_rate.append(a1)
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+ volt_rate.append(a1)
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# plt.plot(xtime1,y1,label='单体电压'+str(i+1))
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# plt.xlabel('时间', fontsize=25)
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# plt.ylabel('SOC差', fontsize=25)
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@@ -147,13 +148,15 @@ class SafetyWarning:
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mk_z_list.append(mk_res.z)
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mk_Tau_list.append(mk_res.Tau)
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mk_slope_list.append(mk_res.slope)
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+ mk_s_list.append(mk_res.s)
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+ mk_svar_list.append(mk_res.var_s)
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"""
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trend:趋势;
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h:有无趋势;
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p:趋势的显著水平,越小趋势越明显;
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z:检验统计量,正代表随时间增大趋势,负代表随时间减小趋势;
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Tau:反映两个序列的相关性,接近1的值表示强烈的正相关,接近-1的值表示强烈的负相关;
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- s:如果S是一个正数,那么后一部分的观测值相比之前的观测值会趋向于变大;如果S是一个负数,那么后一部分的观测值相比之前的观测值会趋向于变小
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+ s:Mann-Kendal的分数,如果S是一个正数,那么后一部分的观测值相比之前的观测值会趋向于变大;如果S是一个负数,那么后一部分的观测值相比之前的观测值会趋向于变小
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slope:趋势斜率
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"""
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# print('单体电压{}:\n'.format(i+1), mk_res)
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@@ -167,6 +170,8 @@ class SafetyWarning:
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mk_z_list.append(0)
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mk_Tau_list.append(0)
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mk_slope_list.append(0)
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+ mk_s_list.append(0)
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+ mk_svar_list.append(0)
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#电芯SOC排名判断.............................................................................
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if not self.df_uniform.empty:
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@@ -189,8 +194,9 @@ class SafetyWarning:
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df_res.loc[0]=[time_now, time_sp, self.sn, faultcode, faultlv, faultinfo, faultadvice]
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break
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else:
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- pass
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+ pass
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+ # plt.show()
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#电池电压变化率离群度计算...............................................................................
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volt_rate_std=np.std(volt_rate)
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volt_rate_mean=np.mean(volt_rate)
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@@ -199,7 +205,11 @@ class SafetyWarning:
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#mk离群度计算
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mk_slope_std=np.std(mk_slope_list)
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mk_slope_mean=np.mean(mk_slope_list)
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- mk_slope_3sigma=(np.array(mk_slope_list)-mk_slope_mean)/mk_slope_std
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+ mk_slope_3sigma=(np.array(mk_slope_list)-mk_slope_mean)/mk_slope_std
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+
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+ # mk_s_std=np.std(mk_s_list)
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+ # mk_s_mean=np.mean(mk_s_list)
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+ # mk_s_3sigma=(np.array(mk_s_list)-mk_s_mean)/mk_s_std
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mk_z_std=np.std(mk_z_list)
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mk_z_mean=np.mean(mk_z_list)
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@@ -227,20 +237,20 @@ class SafetyWarning:
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#mana-kendall趋势检测
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for i in range(len(mk_p_list)):
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#适用动态工况判断
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- if mk_trend_list[i]=='decreasing' and mk_p_list[i]<self.param.mk_p and mk_z_list[i]<self.param.mk_z and mk_Tau_list[i]<self.param.mk_Tau and mk_slope_3sigma[i]<-3 and mk_slope_list[i]<self.param.mk_slope and abs(cellsoh_3sigma[i])<2.5:
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+ if mk_trend_list[i]=='decreasing' and mk_p_list[i]<self.param.mk_p and mk_z_list[i]<self.param.mk_z and mk_Tau_list[i]<self.param.mk_Tau and mk_slope_3sigma[i]<-3 and mk_slope_list[i]<self.param.mk_slope and abs(cellsoh_3sigma[i])<2.5 and volt_rate_3sigma[i]<-3:
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faultcode=110
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faultlv=4
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faultinfo='电芯{}发生热失控安全预警'.format(i+1)
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faultadvice='2联系用户远离电池,立刻召回电池'
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df_res.loc[0]=[time_now, time_sp, self.sn, faultcode, faultlv, faultinfo, faultadvice]
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#适用静态工况判断
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- elif self.celltype<=50 and mk_trend_list[i]=='decreasing' and mk_p_list[i]<self.param.mk_p and mk_z_list[i]<-6 and (mk_Tau_list[i]<-0.9 or mk_z_3sigma[i]<-3) and mk_slope_3sigma[i]<-3.5 and mk_slope_list[i]<-0.025:
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+ elif self.celltype<=50 and mk_trend_list[i]=='decreasing' and mk_p_list[i]<self.param.mk_p and mk_z_list[i]<-6 and (mk_Tau_list[i]<-0.9 or mk_z_3sigma[i]<-3) and mk_slope_3sigma[i]<-3.5 and mk_slope_list[i]<-0.025 and volt_rate_3sigma[i]<-3:
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faultcode=110
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faultlv=4
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faultinfo='电芯{}发生热失控安全预警'.format(i+1)
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faultadvice='2联系用户远离电池,立刻召回电池'
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df_res.loc[0]=[time_now, time_sp, self.sn, faultcode, faultlv, faultinfo, faultadvice]
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- elif self.celltype>50 and mk_trend_list[i]=='decreasing' and mk_p_list[i]<self.param.mk_p and mk_z_list[i]<-6 and (mk_Tau_list[i]<-0.9 or mk_z_3sigma[i]<-3) and mk_slope_3sigma[i]<-3.5 and mk_slope_list[i]<-0.25:
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+ elif self.celltype>50 and mk_trend_list[i]=='decreasing' and mk_p_list[i]<self.param.mk_p and mk_z_list[i]<-6 and (mk_Tau_list[i]<-0.9 or mk_z_3sigma[i]<-3) and mk_slope_3sigma[i]<-3.5 and mk_slope_list[i]<-0.25 and volt_rate_3sigma[i]<-3:
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faultcode=110
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faultlv=4
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faultinfo='电芯{}发生热失控安全预警'.format(i+1)
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@@ -249,5 +259,4 @@ class SafetyWarning:
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else:
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pass
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- # plt.show()
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return df_res
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