Partial discharge signal extracting using the empirical mode decomposition with wavelet transform

Mei Yan Lin, Cheng-Chi Tai, Ya Wen Tang, Ching Chau Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Empirical mode decomposition (EMD) has good adaptivity for non-stationary and nonlinear signal analysis. This paper uses the advantage of EMD and combines with the wavelet transform (EMD-WT) to extract partial discharge (PD) signals in noises. The wavelet transform is a common used method for PD signal denoising. However, once the signal to noise ratio (SNR) decreases seriously, the WT method will be failed. Compare to the WT method, the EMD-WT has better performance for noise reduction. It has been verified that the EMD-WT method can preserve more information even though the SNR is low. The results show that the EMD-WT is suitable for PD denoising in a noisy environment.

Original languageEnglish
Title of host publication2011 7th Asia-Pacific International Conference on Lightning, APL2011
Pages420-424
Number of pages5
DOIs
Publication statusPublished - 2011 Dec 1
Event2011 7th Asia-Pacific International Conference on Lightning, APL2011 - Chengdu, China
Duration: 2011 Nov 12011 Nov 4

Publication series

Name2011 7th Asia-Pacific International Conference on Lightning, APL2011

Other

Other2011 7th Asia-Pacific International Conference on Lightning, APL2011
CountryChina
CityChengdu
Period11-11-0111-11-04

Fingerprint

Partial discharges
Wavelet transforms
wavelet
transform
decomposition
Decomposition
signal-to-noise ratio
Signal to noise ratio
Signal denoising
Signal analysis
Noise abatement
method

All Science Journal Classification (ASJC) codes

  • Environmental Chemistry

Cite this

Lin, M. Y., Tai, C-C., Tang, Y. W., & Su, C. C. (2011). Partial discharge signal extracting using the empirical mode decomposition with wavelet transform. In 2011 7th Asia-Pacific International Conference on Lightning, APL2011 (pp. 420-424). [6110158] (2011 7th Asia-Pacific International Conference on Lightning, APL2011). https://doi.org/10.1109/APL.2011.6110158
Lin, Mei Yan ; Tai, Cheng-Chi ; Tang, Ya Wen ; Su, Ching Chau. / Partial discharge signal extracting using the empirical mode decomposition with wavelet transform. 2011 7th Asia-Pacific International Conference on Lightning, APL2011. 2011. pp. 420-424 (2011 7th Asia-Pacific International Conference on Lightning, APL2011).
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title = "Partial discharge signal extracting using the empirical mode decomposition with wavelet transform",
abstract = "Empirical mode decomposition (EMD) has good adaptivity for non-stationary and nonlinear signal analysis. This paper uses the advantage of EMD and combines with the wavelet transform (EMD-WT) to extract partial discharge (PD) signals in noises. The wavelet transform is a common used method for PD signal denoising. However, once the signal to noise ratio (SNR) decreases seriously, the WT method will be failed. Compare to the WT method, the EMD-WT has better performance for noise reduction. It has been verified that the EMD-WT method can preserve more information even though the SNR is low. The results show that the EMD-WT is suitable for PD denoising in a noisy environment.",
author = "Lin, {Mei Yan} and Cheng-Chi Tai and Tang, {Ya Wen} and Su, {Ching Chau}",
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Lin, MY, Tai, C-C, Tang, YW & Su, CC 2011, Partial discharge signal extracting using the empirical mode decomposition with wavelet transform. in 2011 7th Asia-Pacific International Conference on Lightning, APL2011., 6110158, 2011 7th Asia-Pacific International Conference on Lightning, APL2011, pp. 420-424, 2011 7th Asia-Pacific International Conference on Lightning, APL2011, Chengdu, China, 11-11-01. https://doi.org/10.1109/APL.2011.6110158

Partial discharge signal extracting using the empirical mode decomposition with wavelet transform. / Lin, Mei Yan; Tai, Cheng-Chi; Tang, Ya Wen; Su, Ching Chau.

2011 7th Asia-Pacific International Conference on Lightning, APL2011. 2011. p. 420-424 6110158 (2011 7th Asia-Pacific International Conference on Lightning, APL2011).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Empirical mode decomposition (EMD) has good adaptivity for non-stationary and nonlinear signal analysis. This paper uses the advantage of EMD and combines with the wavelet transform (EMD-WT) to extract partial discharge (PD) signals in noises. The wavelet transform is a common used method for PD signal denoising. However, once the signal to noise ratio (SNR) decreases seriously, the WT method will be failed. Compare to the WT method, the EMD-WT has better performance for noise reduction. It has been verified that the EMD-WT method can preserve more information even though the SNR is low. The results show that the EMD-WT is suitable for PD denoising in a noisy environment.

AB - Empirical mode decomposition (EMD) has good adaptivity for non-stationary and nonlinear signal analysis. This paper uses the advantage of EMD and combines with the wavelet transform (EMD-WT) to extract partial discharge (PD) signals in noises. The wavelet transform is a common used method for PD signal denoising. However, once the signal to noise ratio (SNR) decreases seriously, the WT method will be failed. Compare to the WT method, the EMD-WT has better performance for noise reduction. It has been verified that the EMD-WT method can preserve more information even though the SNR is low. The results show that the EMD-WT is suitable for PD denoising in a noisy environment.

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Lin MY, Tai C-C, Tang YW, Su CC. Partial discharge signal extracting using the empirical mode decomposition with wavelet transform. In 2011 7th Asia-Pacific International Conference on Lightning, APL2011. 2011. p. 420-424. 6110158. (2011 7th Asia-Pacific International Conference on Lightning, APL2011). https://doi.org/10.1109/APL.2011.6110158