Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPWRD.2004.832398
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dc.titleAnalysis of UHF signal using prediction model
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.accessioned2014-10-07T04:23:49Z
dc.date.available2014-10-07T04:23:49Z
dc.date.issued2004-10
dc.identifier.citationChang, C., Chang, C.S., Jin, J., Hoshino, T., Hanai, M., Kobayashi, N. (2004-10). Analysis of UHF signal using prediction model. IEEE Transactions on Power Delivery 19 (4) : 1579-1586. ScholarBank@NUS Repository. https://doi.org/10.1109/TPWRD.2004.832398
dc.identifier.issn08858977
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/81967
dc.description.abstractWith increasing interest in the reduction of cost for operation and maintenance of SF6 gas-insulated switchgear (GIS), various methods of condition monitoring have been developed and used in conjunction with highly sensitive sensors and advanced digital signal processing techniques. Detection of partial-discharge signals in GIS using ultra-high frequency (UHF) technique has gained wide acceptance in research and industry. Unlike approaches of fast Fourier transformation and discrete wavelet transformation (DWT), a novel method of using an adaptive linear combiner as a prediction model to analyze UHF signals is introduced in this paper. Successful results are obtained by applying this new method on field data measured by a UHF coupler. The feasibility of this new approach is studied and proved by the statistical distributions of the trained weights. © 2004 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TPWRD.2004.832398
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TPWRD.2004.832398
dc.description.sourcetitleIEEE Transactions on Power Delivery
dc.description.volume19
dc.description.issue4
dc.description.page1579-1586
dc.description.codenITPDE
dc.identifier.isiut000224278600008
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