Selection of the optimal wavelet bases for wavelet de-noising of partial discharge signal

Based on analyzing the influence of wavelet bases selection on the quality of wavelet de-noising, this paper presents a novel method for selecting the best wavelet bases for signal de-noising in partial discharge signal (PDS) processing. The correlation coefficient as well as the signal-to-noise ratio is used for evaluating the optimal wavelet base at present. These two indexes, statistics of meaning, can not reveal the performance of wavelet de-noising comprehensively. In this paper, the concept of information loss assessing coefficient is proposed on the foundation of some contents of wavelet threshold de-noising for the first time, and it is more suited to further analyzing the quality of partial discharge signal. The method is applied during the numerical simulating signals and corona discharge acquisition. From the results it shows that the de-noising procedure can be further refined in selecting the optimal wavelet bases.