A Substation UHF Partial Discharge Detection Method Based on Maximum Likelihood Estimation

Partial discharge is one of the early signs of insulation degradation in power equipment. Accurate detection of partial discharge is of great significance to the safe and stable operation of electrical equipment. Most existing researches focus on the analyzing and processing of partial discharge signal waveform to solve the problem of substation noise interference. In this paper, the partial discharge detection problem is transformed into a statistical analysis problem, and the maximum likelihood estimation method in probability statistics is used to achieve the accurate direction of arrival (DOA) estimation of ultra-high frequency partial discharge sources in low signal-to-noise ratio (SNR) environment. The simulation and field tests results showed that the proposed method can improve the partial discharge DOA estimation accuracy, especially in the substation environment with high interference and low SNR (signal-to-noise ratio is about 5dB). The DOA estimation accuracy is improved 20% compared to the traditional MUSIC algorithm. This paper provides a new idea for solving the partial discharge detection and DOA estimation problem by using probability and statistics methods.