Feature extraction of arc high impedance grounding fault of low-voltage distribution lines based on Bayesian network optimisation algorithm

In order to accurately extract the fault features of arc high impedance grounding of low-voltage distribution lines and judge the fault feature types of arc high impedance grounding of low-voltage distribution lines, a fault feature extraction method for arc high impedance grounding of low-voltage distribution lines based on Bayesian network optimisation algorithm is proposed. According to the model of arc high impedance grounding fault based on Thomson’s principle, the parameter information of each transmission signal in arc high impedance grounding fault is extracted. Through the denoising method of arc high impedance grounding signal based on combined filter, the noise information of transmission signal in case of arc high impedance grounding fault is removed and the signal purity is improved. The detection and recognition method for fault characteristics of arc high impedance grounding of low-voltage distribution lines based on Bayesian network optimisation algorithm is used to detect and judge the fault characteristics of the abnormal characteristics of the denoised transmission signal, and complete the fault feature extraction. After testing, this method can accurately and real-time extract the fault characteristics of arc high impedance grounding of low-voltage distribution lines, and has application value.