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dc.contributor.authorAljohani, O.
dc.contributor.authorAbu-Siada, Ahmed
dc.contributor.authorLi, S.
dc.date.accessioned2017-03-15T22:27:18Z
dc.date.available2017-03-15T22:27:18Z
dc.date.created2017-03-14T06:55:54Z
dc.date.issued2016
dc.identifier.citationAljohani, O. and Abu-Siada, A. and Li, S. 2016. High frequency power transformer modelling for frequency response analysis studies, International Conference on Condition Monitoring and Diagnosis (CMD), 25-28 Sept. 2016, pp. 291-294.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/50616
dc.identifier.doi10.1109/CMD.2016.7757818
dc.description.abstract

Frequency response analysis (FRA) has been widely utilized to detect winding and core deformations within power transformers. While the measurement technique has been well-developed and standardized, the interpretation of the FRA signature is still a challenging area that calls for more research, in order to establish standard and widely-accepted interpretation codes. To investigate the impact of various winding deformations on the transformer FRA signature, a reliable high frequency transformer model is required. This paper presents two high frequency transformer models based on the electrical distributed parameters circuit and numerical representation that are to be used for FRA studies. The electrical parameters used in both models are obtained through simulating a 10-kVA transformer using a three-dimensional finite element analysis, so as to mimic a transformer's real operation. The calculated parameters are then employed within the two proposed models to acquire FRA signatures which are then analyzed and compared. The results show that both methods are suitable to model power transformers for FRA studies. © 2016 IEEE.

dc.titleHigh frequency power transformer modelling for frequency response analysis studies
dc.typeConference Paper
dcterms.source.startPage291
dcterms.source.endPage294
dcterms.source.titleCMD 2016 - International Conference on Condition Monitoring and Diagnosis
dcterms.source.seriesInternational Conference on Condition Monitoring and Diagnosis (CMD)
dcterms.source.isbn9781509033980
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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