卜树坡.基于超阈值分布的直流充电桩计量准确性预测研究[J].电测与仪表,2021,58(10):145-150. Bu Shupo.Research on Prediction of Measurement Accuracy of DC Charging Pile Based on Over-threshold Distribution[J].Electrical Measurement & Instrumentation,2021,58(10):145-150.
基于超阈值分布的直流充电桩计量准确性预测研究
Research on Prediction of Measurement Accuracy of DC Charging Pile Based on Over-threshold Distribution
In order to control the quality of the electric energy meter manufacturing process. BP neural network is introduced as the classification tool of the abnormal subject pattern set. The longest common subsequence algorithm and the central time series algorithm are used to measure the similarity of the abnormal subject pattern set and extract the fault features. Finally, the correlation among 7 typical failure features with high frequency is analyzed to determine the cause of the rise of defective product rate. The results show that this method can analyze the fault causes, which is of great guiding significance for improving the quality of watt hour meter.
