De-noising of partial discharge ultrasonic signal of insulation bar in large motor based on GMC-wavelet

Abstract In view of the bad operation environment large motor, which often suffers from various strong noise interference, partial discharge ultrasonic signal is annihilated, makes it difficult to detect and analyse. A de-noising method based on generalized minimax concavity (GMC) wavelet for (PD) proposed. GMC used enhance sparsity PD eliminate high-frequency at same time. Then residual sparse low-frequency former are de-noised again combined with wavelet. Finally, reconstructed achieve purpose original noise. Compared ℓ 1 -norm method, -norm-wavelet simulation results show that time domain analysis, effect proposed obviously better than other four methods. The SNR MSE those latter. addition, insulation bar model motor constructed obtain actual signal, further verifies its effectiveness, also This can not only target improve estimation accuracy, but effect, while retaining effective information characteristics. provide new ideas types de-noising, lay foundation later feature analysis.