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Autonomous localization of partial discharge sources within large transformer windings

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dc.citedby16
dc.contributor.authorRahman M.S.A.en_US
dc.contributor.authorLewin P.L.en_US
dc.contributor.authorRapisarda P.en_US
dc.contributor.authorid36609854400en_US
dc.contributor.authorid7102386669en_US
dc.contributor.authorid57207558453en_US
dc.date.accessioned2023-05-29T06:12:24Z
dc.date.available2023-05-29T06:12:24Z
dc.date.issued2016
dc.descriptionCondition monitoring; Digital radio; Impulse response; Partial discharges; Power transformers; Principal component analysis; Signal processing; Wavelet transforms; Winding; Different frequency; Electrical detection method; Health informations; Monitoring hardware; Partial discharge sources; Power transformer insulation; Radio frequency current transducer; Source localization; Transformer windingsen_US
dc.description.abstractPartial discharge (PD) condition monitoring inside a HV transformer generally and particularly along a transformer winding has become an important research area with the ultimate aim of providing asset health information that enables maintenance and replacement processes to be carried out effectively. As far as PD activity inside transformer windings is concerned, an electrical detection method has been developed based on the use of radio frequency current transducers and subsequent digital signal processing of captured measurement data. A localization approach based on the measurement of currents at the bushing tap point and neutral to earth connection has been developed, with the assumption that different PD source locations will generate unique signal profiles in terms of the distribution of measured current energies with respect to both frequency and time. Therefore the technique presented is based on analysis of measured current energies associated with different frequencies. Principal Component Analysis (PCA) is then applied to reduce the dimensionality of the data, whilst minimizing lost information in the original dataset. This non-linear analysis of captured current data is not practicable for the field but the process can be represented through the use of three finite impulse response filters that have the ability to perform PD source localization automatically and are straightforward to implement in monitoring hardware. � 1994-2012 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7480674
dc.identifier.doi10.1109/TDEI.2015.005070
dc.identifier.epage1098
dc.identifier.issue2
dc.identifier.scopus2-s2.0-84973472779
dc.identifier.spage1088
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84973472779&doi=10.1109%2fTDEI.2015.005070&partnerID=40&md5=2617c8562f82ddb90b6d4d1ef987beb9
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22810
dc.identifier.volume23
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleIEEE Transactions on Dielectrics and Electrical Insulation
dc.titleAutonomous localization of partial discharge sources within large transformer windingsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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