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dc.contributor.authorAljohani, O.
dc.contributor.authorAbu-Siada, Ahmed
dc.date.accessioned2017-03-15T22:27:21Z
dc.date.available2017-03-15T22:27:21Z
dc.date.created2017-03-14T06:55:54Z
dc.date.issued2015
dc.identifier.citationAljohani, O. and Abu-Siada, A. 2015. Minimum detection of power transformer short circuit fault using frequency response analysis, Australasian Universities Power Engineering Conference: Challenges for Future Grids (AUPEC 2015), 27-30 Sept. 2015.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/50639
dc.identifier.doi10.1109/AUPEC.2015.7324789
dc.description.abstract

The majority of mechanical deformation within power transformers is due to short circuit faults. Although, frequency response analysis (FRA) has been recently recognized as the most reliable detection tool for mechanical deformation in transformers, in the event of minor fault, the current FRA interpretation approach may not able to detect any variations between healthy and faulty FRA signatures. This paper is aimed at identifying the minimum level of short circuit fault within power transformer that can be detected using FRA technique. In this regard, the physical geometrical dimension of a three-phase transformer has been simulated using three-dimensional finite element analysis to emulate the physical operating conditions of power transformers. Short-circuit faults within transformer winding are simulated at several fault levels and the FRA signature for each case study is obtained and compared with the healthy signature. Results show that there is a minimum detection level of short circuit faults that can be detected using FRA technique.

dc.titleMinimum detection of power transformer short circuit fault using frequency response analysis
dc.typeConference Paper
dcterms.source.titleAustralasian Universities Power Engineering Conference: Challenges for Future Grids (AUPEC 2015)
dcterms.source.series2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids, AUPEC 2015
dcterms.source.isbn9781479987252
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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