Automatic fault location method for power communication network based on a machine learning algorithm

Abstract

The current conventional automatic fault location method of power communication network mainly realizes the identification of faulty branches by calculating node power parameters, which leads to poor location effects due to the lack of effective analysis of fault signal data. In this regard, the automatic fault location method of the store head communication network based on a machine learning algorithm is proposed. Firstly, the fault signal data are collected and pre-processed, specifically including data cleaning and data format conversion, and then the individual fault signal is used as the basis to differentiate the weight parameters of different abnormal degrees and combine with the state threshold to realize the judgment of the fault node interval location. In the experiments, the fault location performance of the proposed method is verified. The experimental results show that when the proposed method is used for fault location, the relative positioning error value of the method is small and has a high fault location accuracy.