Partial discharge monitoring in a noisy environment

A. M. Gaouda, A. H. El-Hag, M. M.A. Salama

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

Abstract

Defining the resolution levels where a PD signal is localized and selecting an automated threshold values for on-line de-noising and measurement are the main challenging task in wavelet multi-resolution analysis (WMRA) application for PD detection and measurement. This paper proposes a new wavelet-based technique for monitoring PD signals embedded in high noise levels. The data is decomposed while sliding into Kaiser's window. Only the maximum coefficients extracted at each resolution level are used to extract the PD signal from noise and measure its magnitude. No thresholding or reconstructions of the thresholded coefficients are required. The extracted data-size of PD signal is very small as compared with actual signal. The proposed monitoring technique is applied on simulated data and laboratory data and gave good results. The simulated data are constructed by using real noise collected from laboratory measurements.

Original languageEnglish
Title of host publicationProceedings of 2008 International Conference on Condition Monitoring and Diagnosis, CMD 2008
PublisherIEEE Computer Society
Pages1048-1051
Number of pages4
ISBN (Print)9781424416219
DOIs
Publication statusPublished - Jan 1 2008
Event2008 International Conference on Condition Monitoring and Diagnosis, CMD 2008 - Beijing, China
Duration: Apr 21 2008Apr 24 2008

Publication series

NameProceedings of 2008 International Conference on Condition Monitoring and Diagnosis, CMD 2008

Other

Other2008 International Conference on Condition Monitoring and Diagnosis, CMD 2008
Country/TerritoryChina
CityBeijing
Period4/21/084/24/08

Keywords

  • De-noising
  • Partial discharge
  • Wavelet

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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