Partial Discharge Signal Denoising Based on Wavelet Pair and Block Thresholding
Siyuan Zhou, Ju Tang, Cheng Pan, Yang Luo, Kailai Yan
Abstract
In electrical engineering, it is of great importance to monitor partial discharge (PD) of high voltage apparatus. However, on-site PD signal easily gets corrupted by white noise, and hence denoising the measured PD signal is necessary to acquire pure PD. In traditional method, single wavelet and regular thresholding are utilized. By combining wavelets of the same family, dual-tree complex wavelet pairs can be constructed. Specific combinations are approximately translation invariant, and they are also able to achieve better denoising effect without sophisticated computation. Meanwhile, considering the correlation between adjacent wavelet coefficients, the block thresholding is employed. In this paper, it is proposed to combine wavelet pair and block thresholding for PD denoising. There are four combinations based on single wavelet/wavelet pair and regular thresholding/block thresholding, and they are compared with each other. Based on a numerical study, the results demonstrate that the proposed algorithm outperforms the traditional method.