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 a lot of noise. Therefore, this paper proposes a novel method by integrating the flower pollination algorithm, variational mode de...

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Bibliographic Details
Published inEnergies (Basel) Vol. 15; no. 21; p. 8167
Main Authors Yang, Jingjie, Yan, Ke, Wang, Zhuo, Zheng, Xiang
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2022
Subjects
Algorithms
denoising
Electric fault location
Electrical equipment and supplies
Electrical machinery
flower pollination algorithm
Kurtosis
Lagrange multiplier
mean envelope entropy
Methods
Narrowband
Noise
Noise reduction
Optimization
partial discharge
Pollination
Population
Safety and security measures
SG filter
Signal monitoring
Signal processing
variational mode decomposition
Wavelet transforms
White noise
China
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15218167