A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition
<p>Simulated the original signal: (<b>a</b>) original PD signal; (<b>b</b>) frequency spectra.</p> "> Figure 2
<p>Simulated the noisy signal: (<b>a</b>) noisy PD signal; (<b>b</b>) frequency spectra.</p> "> Figure 3
<p>Overall process flow diagram of the proposed FPA-VMD-SG denoising method.</p> "> Figure 4
<p>Simulated PD signal decomposition: (<b>a</b>) IMFs; (<b>b</b>) frequency spectra.</p> "> Figure 5
<p>Kurtosis value of each IMF.</p> "> Figure 6
<p>Denoised signal.</p> "> Figure 7
<p>The denoising results of PD signals by different methods: (<b>a</b>) FPA-VMD-SG; (<b>b</b>) EMD-WT; (<b>c</b>) ASVD.</p> "> Figure 8
<p>Real PD signal.</p> "> Figure 9
<p>Real PD signal after mixing noise.</p> "> Figure 10
<p>The denoising results of real PD by different methods: (<b>a</b>) FPA-VMD-SG; (<b>b</b>) EMD-WT; (<b>c</b>) ASVD.</p> ">
Abstract
:1. Introduction
2. Basic Theory
2.1. Variational Mode Decomposition
2.2. Flower Pollination Algorithms
2.3. Envelope Entropy
2.4. Kurtosis
2.5. Savitzky–Golay Filter
2.6. Threshold Denoising
3. Denoising Method
3.1. Simulated PD Signal
3.2. Proposed FPA-VMD-SG Denoising Method
3.3. Simulated PD Signal Denoising
4. Comparison and Analysis of Denoising
4.1. Denoising Results of Simulated PD Signal
4.2. Denoising Results of Real PD Signal
5. Conclusions
- (1)
- Based on the MME, the appropriate parameters . and of VMD could be found by FPA.
- (2)
- The VMD had excellent anti-modal mixing characteristics, which could decompose the PD noise signal properly.
- (3)
- The SG filter could effectively remove the noise in the noise component and retain the PD signal.
- (4)
- The FPA-VMD-SG method could effectively suppress white noise and narrowband noise in the PD signal.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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PD Pulse | |||
---|---|---|---|
10 | 100 | 0.5 | |
10 | 100 | 0.5 | |
10 | 100 | 2 | |
10 | 100 | 2 |
SNR | NCC | RMSE | |
---|---|---|---|
EMD-WT | 5.8567 | 0.2310 | 0.520 |
ASVD | 5.9344 | 0.6007 | 0.0413 |
FPA-VMD-SG | 8.1584 | 0.7020 | 0.0399 |
EMD-WT | ASVD | FPA-VMD-SG | |
---|---|---|---|
9.4793 | 10.0246 | 14.5893 |
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Yang, J.; Yan, K.; Wang, Z.; Zheng, X. A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition. Energies 2022, 15, 8167. https://doi.org/10.3390/en15218167
Yang J, Yan K, Wang Z, Zheng X. A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition. Energies. 2022; 15(21):8167. https://doi.org/10.3390/en15218167
Chicago/Turabian StyleYang, Jingjie, Ke Yan, Zhuo Wang, and Xiang Zheng. 2022. "A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition" Energies 15, no. 21: 8167. https://doi.org/10.3390/en15218167
APA StyleYang, J., Yan, K., Wang, Z., & Zheng, X. (2022). A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition. Energies, 15(21), 8167. https://doi.org/10.3390/en15218167