A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition

Partial discharge (PD) online monitoring is a common technique for high-voltage equipment diagnosis. However, due to field interference, the monitored PD signal contains lot of noise. Therefore, this paper proposes novel method by integrating flower pollination algorithm, variational mode decomposition, and Savitzky–Golay filter (FPA-VMD-SG) effectively suppress white noise narrowband in signal. Firstly, based on mean envelope entropy (MEE), decomposition number quadratic penalty term VMD were optimized FPA. The containing was broken down into intrinsic functions (IMFs) parameters. Secondly, IMFs classified as component, dominant component according kurtosis value. Thirdly, denoised using SG filter, mixed with reconstruct new Finally, threshold denoising used eliminate residual To verify performance FPA-VMD-SG method, compared empirical wavelet transform (EMD-WT) adaptive singular value (ASVD), results simulated real signals indicated that had excellent performance.