Extraction of Partial Discharge Pulses from the Complex Noisy Signals of Power Cables Based on CEEMDAN and Wavelet Packet
Abstract
:1. Introduction
2. PD Signal Extraction Based on the CEEMDAN Algorithm
2.1. CEEMDAN Algorithm
2.2. Effective Selection of Significant IMFs
3. Adaptive Wavelet Packet Threshold Method
4. Signal Extraction Algorithm Based on Combined CEEMDAN-Hankel-SVD
- Apply CEEMDAN to a noisy PD signal and obtain N IMFs.
- Construct a Hankel matrix for each IMF and accordingly apply SVD. The singular values characteristic of periodic narrowband noise are set to zero and the PD signal is reconstructed from the set of IMFs with the periodic narrowband noise removed.
- Calculate the cross-correlation between each remaining IMF and the original signal and accordingly extract the significant IMFs.
- The PD signal is finally reconstructed from the significant IMFs and the residual white noise in the reconstructed signal is suppressed using the improved wavelet packet threshold method.
5. Results and Discussion
5.1. PD Signal Simulation
5.2. PD Signal Extraction and Discussion
- 1
- The proposed CEEMDAN-Hankel-SVD-based PD signal extraction method provides a high SNR after extraction with no significant distortion in the waveform and low energy loss.
- 2
- The CEEMD-based extraction method suppresses the noise in the signal well. However, the loss of signal energy is excessive.
- 3
- The VMD wavelet threshold method is consistent with the value of fc adopted in the PD signal. Therefore, the periodic narrowband interference cannot be filtered out. Consequently, this method fails to achieve a good signal extraction effect.
5.3. Stability Analysis of Algorithm for White Noise
5.4. Measured PD Pulse Detection for Arrival Time Assessment on Different SNR
6. Conclusions
- 1
- The CEEMDAN-Hankel-SVD algorithm suppresses frequency aliasing and periodic narrowband interference in synthesized PD signals.
- 2
- Compared with the VMD wavelet threshold method, the CEEMDAN-Hankel-SVD method has no frequency limitations for the periodic narrowband noise that can be filtered out, and noisy PD signals can be adaptively decomposed.
- 3
- The threshold function employed in the improved wavelet packet threshold method combines the advantages of soft and hard thresholds and not only accurately preserves the continuity of the PD signal, but also reduces the constant deviation between the wavelet coefficient of the noisy signal and the estimated noise-free wavelet coefficient. Accordingly, the noise-free PD signal was extracted with high fidelity. Therefore, the proposed approach lays a good foundation for conducting subsequent work on signal pattern recognition and fault localization.
- 4
- The time-varying kurtosis method obtains highly accurate arrival times when applied to PD signals extracted by the proposed CEEMDAN-Hankel-SVD method from synthesized signals in complex noise environments with low SNR values.
Author Contributions
Funding
Conflicts of Interest
References
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Evaluation Parameter | Signal Extraction Method | Pulse 1 | Pulse 2 |
---|---|---|---|
SNR | Method of this paper | 16.2860 | 14.9465 |
CEEMD | 1.3714 | 7.7682 | |
VMD wavelet threshold method | 1.8403 | 3.7937 | |
NCC | Method of this paper | 0.9927 | 0.9940 |
CEEMD | 0.8313 | 0.5842 | |
VMD wavelet threshold method | 0.6551 | 0.8328 | |
VTP | Method of this paper | 0.9787 | 1.0134 |
CEEMD | 1.4194 | 1.1698 | |
VMD wavelet threshold method | 0.7166 | 0.7888 | |
Amplitude relative error (%) | Method of this paper | 0.8 | 1.68 |
CEEMD | 32.68 | 11.53 | |
VMD wavelet threshold method | 7.95 | 14.90 |
SNR | –6 dB | –9 dB | –14 dB | –23 dB | Manual Picking |
---|---|---|---|---|---|
Point | 262 | 263 | 263 | 263 | 262 |
ρNRR | 88.8097 | 98.4420 | 116.9203 | 148.3636 | - |
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Sun, K.; Zhang, J.; Shi, W.; Guo, J. Extraction of Partial Discharge Pulses from the Complex Noisy Signals of Power Cables Based on CEEMDAN and Wavelet Packet. Energies 2019, 12, 3242. https://doi.org/10.3390/en12173242
Sun K, Zhang J, Shi W, Guo J. Extraction of Partial Discharge Pulses from the Complex Noisy Signals of Power Cables Based on CEEMDAN and Wavelet Packet. Energies. 2019; 12(17):3242. https://doi.org/10.3390/en12173242
Chicago/Turabian StyleSun, Kang, Jing Zhang, Wenwen Shi, and Jingdie Guo. 2019. "Extraction of Partial Discharge Pulses from the Complex Noisy Signals of Power Cables Based on CEEMDAN and Wavelet Packet" Energies 12, no. 17: 3242. https://doi.org/10.3390/en12173242