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dc.contributor.authorMa, Hui
dc.contributor.authorSaha, Tapan
dc.contributor.authorEkanayake, Chandima
dc.contributor.editorProf. Arindum Ghosh
dc.date.accessioned2018-01-04T05:26:25Z
dc.date.available2018-01-04T05:26:25Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10072/173621
dc.description.abstractPower transformers are one of the most critical equipments in electricity network. A number of techniques such as dissolved gas analysis (DGA), polarization and depolarization currents (PDC) measurement and frequency domain spectroscopy (FDS) have been adopted across utilities for transformer insulation diagnosis. However, there are still considerable challenges remaining in interpreting measured data of these techniques. This paper develops machine learning algorithms, which utilise archived data for making insulation diagnosis on the transformer of interest. Analysis and interpretation of field test data are presented in the paper.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherAustralasian Universities Power Engineering Conference
dc.publisher.placeBrisbane, Australia
dc.publisher.urihttp://ieeexplore.ieee.org/abstract/document/6102514/
dc.relation.ispartofconferencenameAUPEC 2011
dc.relation.ispartofconferencetitleAustralasian Universities Power Engineering Conference: integrating renewables into the grid
dc.relation.ispartofdatefrom2011-09-25
dc.relation.ispartofdateto2011-09-28
dc.relation.ispartoflocationBrisbane, Australia
dc.subject.fieldofresearchElectrical and Electronic Engineering not elsewhere classified
dc.subject.fieldofresearchcode090699
dc.titleMachine learning techniques for power transformer insulation diagnosis
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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gro.griffith.authorEkanayake, Chandima MB.


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    Contains papers delivered by Griffith authors at national and international conferences.

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