Please use this identifier to cite or link to this item: https://doi.org/10.1109/TDEI.2006.1667751
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dc.titleOnline source recognition of partial discharge for gas insulated substations using independent component analysis
dc.contributor.authorChang, C.S.
dc.contributor.authorJin, J.
dc.contributor.authorChang, C.
dc.contributor.authorHoshino, T.
dc.contributor.authorHanai, M.
dc.contributor.authorKobayashi, N.
dc.date.accessioned2014-10-07T04:33:56Z
dc.date.available2014-10-07T04:33:56Z
dc.date.issued2006-08
dc.identifier.citationChang, C.S., Jin, J., Chang, C., Hoshino, T., Hanai, M., Kobayashi, N. (2006-08). Online source recognition of partial discharge for gas insulated substations using independent component analysis. IEEE Transactions on Dielectrics and Electrical Insulation 13 (4) : 892-902. ScholarBank@NUS Repository. https://doi.org/10.1109/TDEI.2006.1667751
dc.identifier.issn10709878
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/82825
dc.description.abstractTo perform reliable insulation diagnosis for gas-insulated substation (GIS), detectable partial discharge (PD) should be identified quickly and effectively. With the increasing application of high voltage dc transmission, PD identification in such systems becomes more and more important. Therefore, a novel technique based on the analysis of ultra high frequency (UHF) resonance waveforms is proposed in this paper to meet the requirement. With the help of independent component analysis, the most dominating features are identified directly from UHF resonance signals without phase information. Using the identified features as the input, a neural network is implemented for recognizing sources of PD in SF6 and separating from the corona in air within a very short time. © 2006 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TDEI.2006.1667751
dc.sourceScopus
dc.subjectCondition monitoring and insula-tion diagnosis
dc.subjectGas insulated substations
dc.subjectIndependent component analysis
dc.subjectOnline source recognition of par-tial discharge and corona
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TDEI.2006.1667751
dc.description.sourcetitleIEEE Transactions on Dielectrics and Electrical Insulation
dc.description.volume13
dc.description.issue4
dc.description.page892-902
dc.description.codenITDIE
dc.identifier.isiut000239705700027
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