Optimization of wavelet and thresholding for partial discharge detection under HVDC

With the rapid development of HVDC technology, the detection and analysis of partial discharge (PD) under HVDC are new challenges to ensure reliable operation of the related power apparatus. The wavelet technique has been proposed for analyzing PD pulses under HVAC and ultra-high frequency signal, but its application for PD under HVDC has not been discussed. This paper dealt with the selection of the optimal wavelet and thresholding for PD pulses in order to apply the wavelet technique to PD detection under HVDC. Four electrode systems, namely protrusion on conductor, protrusion on enclosure, free particle, and crack inside spacer were fabricated to simulate typical defects in a gas insulated switchgear. The detected PD pulses were decomposed by multiresolution analysis. The correlation coefficient and dynamic time warping methods were used to select the optimal wavelet. The optimal threshold and thresholding function were chosen from various combinations with the simulated pulses. The results revealed that processing PD pulses with the mother wavelet of bior2.6, automatic threshold, and intermediate thresholding function presented the best performance.