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

4 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

All Science Journal Classification (ASJC) codes

  • Environmental Chemistry

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