Scale dependent wavelet selection for de-noising of partial discharge detection

Abstract

Wavelet shrinkage methods are effective for de-noising of partial discharge (PD) detection. Base wavelets are related to distortion of PD signals de-noised by wavelet shrinkage methods. This paper presents a scale dependent wavelet selection scheme for de-noising of PD detection. The scale dependent wavelet selection scheme is called the energy based wavelet selection (EBWS) because an energy criterion is proposed for the scheme. In the proposed energy criterion, a base wavelet is selected as an optimal base wavelet if it can generate an approximation with the largest energy among all base wavelets for selection at each scale. PD high-frequency signals are simulated and PD ultra-high-frequency signals are obtained by experiments in laboratory for de-noising experiments and analysis. In comparison with the correlation-based wavelet selection (CBWS) scheme, the wavelet shrinkage, based on the EBWS, generates significantly smaller waveform distortion and magnitude errors of de-noised PD signals.