Adaptive Window Singular Value Decomposition Method Based on Particle Swarm Optimization for Partial Discharge Denoising

Deterioration of insulation materials caused by partial discharge is one of the important reasons for the failure of power equipment. The noise caused by the interference of the external electromagnetic environment seriously affects the accuracy of partial discharge detection. Aiming at the problem of partial discharge noise suppression, this paper proposed a partial discharge signal noise suppression method based on adaptive window singular value decomposition. This method first randomly generated a series of windows with different positions and lengths on the noisy partial discharge signal; Then singular value decomposition method was employed to denoise the signals in each window; Finally, the denoising index was chosen as the fitness function, through the particle swarm algorithm to obtain the optimal solution of the window position and length. The noise signals obtained by simulation and experiment were verified, and the method was compared with adaptive singular value decomposition, wavelet denoising, and other methods. The results showed that this method could achieve a better denoising effect.