Research on partial discharge signal denoising based on Kalman-WPT

Abstract

Abstract Oil-immersed insulating paper will produce partial discharge under high-frequency pulse voltage conditions, so suppressing or reducing the generation of partial discharge signals is an important method for stabilizing the operation of power equipment. However, it has been found in experiments that various interference signals can affect the generation, capture, and measurement of partial discharge signals during various analyses. Therefore, how to capture partial discharge signals effectively and accurately through denoising algorithms has become the focus of this series of experiments. Kalman filtering and wavelet packet transform are the most basic and commonly used methods for denoising at this stage. By analyzing and comparing the basic principles and characteristics of the two methods, the author proposes a Kalman-WPT joint denoising method and conducts simulation analysis using MATLAB 2022b. Multiple controlled experiments have shown that the signal-to-noise ratio of selected discharge signals has increased from 1.3052 for Kalman filtering and 8.9553 for wavelet packet transform to 10.3702, which is sufficient to prove that this method enhances the denoising effect on the original partial discharge signal, reduces waveform distortion, and greatly improves signal detection accuracy.