Research on Partial Discharge Noise Reduction Method of Motor Based on SVD-VMD

Online monitoring of Partial discharge (PD) is an ordinary technology for condition monitoring of high-voltage motor. However, it is difficult because of noise interference on site. Therefore, to solve the problem that the signal of high voltage motor PD is swamped by white Gaussian noise and narrowband periodic interference, a new denoising method combining Singular value decomposition (SVD) and Variational Mode Decomposition (VMD) is proposed. First, the original PD signal is decomposed by SVD. After the Kurtosis of the singular value sequence is calculated, periodic narrowband noise is removed by adaptively selecting the singular value to be reconstructed; Then, the starting position of PD signal is determined by calculating the variance of the signal in the sliding window; The signal after noise removal is obtained by zeroing the no PD location finally. The obtained PD signals are denoised and compared with VMD and EMD-WT. Simulation results show that compared with other denoising methods, SVD-VMD improves signal-to-noise ratio by 30% and has good performance. Simulation results show that compared with other denoising methods, SVD-VMD improves signal-to-noise ratio by 30% and has good performance.