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

Jingjie Yang, Ke Yan, Zhuo Wang and Xiang Zheng ()
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Jingjie Yang: School of Automation and Electrical Engineering, Dalian Jiaotong University, Dalian 116028, China
Ke Yan: Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
Zhuo Wang: School of Automation and Electrical Engineering, Dalian Jiaotong University, Dalian 116028, China
Xiang Zheng: School of Automation and Electrical Engineering, Dalian Jiaotong University, Dalian 116028, China

Energies, 2022, vol. 15, issue 21, 1-12

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

Keywords: variational mode decomposition; flower pollination algorithm; SG filter; mean envelope entropy; denoising; partial discharge (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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