摘要：Partial discharge (PD) of high voltage equipment detected by online monitoring is regarded as a key indicator of insulation status. Threshold estimation exerts an important influence on the denoising effects of PD signals after wavelet-based denoising. In order to improve the adaptive performance of wavelet-based denoising and reduce the distortion of denoised signal, an approach of hybrid particle swarm optimization (HPSO) adaptive wavelet threshold estimation (HPSOTE) is presented in this paper. The effect of four different factors on noise rejection ratio (NRR) is studied. The results show that this HPSOTE can remove the noise effectively and has comparatively high application value in PD online monitoring for smart grid based on big data.
