Self-Adaptive Morphological Filter for Noise Reduction of Partial Discharge Signals

Partial Discharge assessment in the insulation of high voltage equipment is one of the most popular approaches for prevention of the insulation breakdown. In the procedure of this assessment, noise reduction of partial discharge signals to get the original PD signal for accurate evaluation is inevitable. This denoising process shall be carried out such a way that the main features of the partial discharge signal like “amplitude”, “rise time”, “energy” and etc. are kept as much as possible. Wavelet Transform and Mathematical Morphology are the useful signal processing algorithms which are exploited and proposed in literatures for noise reduction of partial discharge signals. In this paper two Wavelet based filters which have promising results are explored and finally compared with the proposed Morphological based filter. Unlike the traditional morphological based filters the advantage of the proposed method is the ability of structure element length selection in a completely self adaptive procedure. Also the results of noise reduction in different noise level are presented that the proposed method shows superiority in all circumstance.