Improved Method to Obtain the Online Impulse Frequency Response Signature of a Power Transformer by Multi Scale Complex CWT
dc.contributor.author | Zhao, Z. | |
dc.contributor.author | Tang, C. | |
dc.contributor.author | Yao, C. | |
dc.contributor.author | Zhou, Q. | |
dc.contributor.author | Xu, L. | |
dc.contributor.author | Gui, Y. | |
dc.contributor.author | Islam, Syed | |
dc.date.accessioned | 2018-12-13T09:14:30Z | |
dc.date.available | 2018-12-13T09:14:30Z | |
dc.date.created | 2018-12-12T02:46:23Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Zhao, Z. and Tang, C. and Yao, C. and Zhou, Q. and Xu, L. and Gui, Y. and Islam, S. 2018. Improved Method to Obtain the Online Impulse Frequency Response Signature of a Power Transformer by Multi Scale Complex CWT. IEEE Access. 6: pp. 48934-48945. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/72813 | |
dc.identifier.doi | 10.1109/ACCESS.2018.2868058 | |
dc.description.abstract |
© 2013 IEEE. Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing fast Fourier transform (FFT) is actually not suitable for processing the transient signals in online IFRA. The field test result also shows that the IFRA signature obtained by FFT is easily distorted by noise. An improved method to obtain the online IFRA signature based on multi-scale complex continuous wavelet transform is proposed. The electrical model simulation and online experiment indicate the superiority of the wavelet transform compared with FFT. This paper provides guidance on the actual application of the online IFRA method. | |
dc.publisher | IEEE Access | |
dc.title | Improved Method to Obtain the Online Impulse Frequency Response Signature of a Power Transformer by Multi Scale Complex CWT | |
dc.type | Journal Article | |
dcterms.source.volume | 6 | |
dcterms.source.startPage | 48934 | |
dcterms.source.endPage | 48945 | |
dcterms.source.issn | 2169-3536 | |
dcterms.source.title | IEEE Access | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
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