Please use this identifier to cite or link to this item: https://doi.org/10.1109/TDEI.2005.1430405
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dc.titleSource classification of partial discharge for gas insulated substation using waveshape pattern recognition
dc.contributor.authorChang, C.
dc.contributor.authorChang, C.S.
dc.contributor.authorJin, J.
dc.contributor.authorHoshino, T.
dc.contributor.authorHanai, M.
dc.contributor.authorKobayashi, N.
dc.date.accessioned2014-10-07T04:36:31Z
dc.date.available2014-10-07T04:36:31Z
dc.date.issued2005-04
dc.identifier.citationChang, C., Chang, C.S., Jin, J., Hoshino, T., Hanai, M., Kobayashi, N. (2005-04). Source classification of partial discharge for gas insulated substation using waveshape pattern recognition. IEEE Transactions on Dielectrics and Electrical Insulation 12 (2) : 374-386. ScholarBank@NUS Repository. https://doi.org/10.1109/TDEI.2005.1430405
dc.identifier.issn10709878
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/83037
dc.description.abstractFrequency-domain analysis of ultra-high frequency (UHF) signals for source identification of partial discharge (PD) occurring in SF 6 inside gas-insulated substation (GIS) has been widely covered in literature. In this, Fast Fourier Transform and Discrete Wavelet Transform based techniques have been extensively applied to derive classifying features from transformed patterns. On the other hand, it appears feasible to develop a time-domain classifier, which derives features directly from the original waveshape. The time-domain classifier is conceptually simple, and requires potentially less computing resources and simpler algorithmic interface with other intelligent techniques due to elimination of frequency-domain transformation. A novel classifier to extract features directly from time-domain waveforms is proposed for classifying SF 6 PD from air corona and among the three types of SF 6 PD, regardless of changes in PD locations and measurement conditions. Three sets of classifying features are proposed. Encouraging results have been achieved with comprehensive experimental data, which verifies and proves the usefulness and feasibility of the time-domain classifier. © 2005 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TDEI.2005.1430405
dc.sourceScopus
dc.subjectGIS
dc.subjectPattern recognition
dc.subjectTime-domain classifier
dc.subjectWaveshape analysis
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TDEI.2005.1430405
dc.description.sourcetitleIEEE Transactions on Dielectrics and Electrical Insulation
dc.description.volume12
dc.description.issue2
dc.description.page374-386
dc.description.codenITDIE
dc.identifier.isiut000228673200017
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