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Feature analysis of numerical calculated data from sweep frequency analysis (SFRA) traces using Self organizing maps

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dc.citedby13
dc.contributor.authorBohari Z.H.en_US
dc.contributor.authorAb Ghani S.A.en_US
dc.contributor.authorBaharom M.F.en_US
dc.contributor.authorNasir M.N.M.en_US
dc.contributor.authorJali M.H.en_US
dc.contributor.authorMd Thayoob Y.H.en_US
dc.contributor.authorid56085889300en_US
dc.contributor.authorid56504019900en_US
dc.contributor.authorid56078250600en_US
dc.contributor.authorid55658799800en_US
dc.contributor.authorid56078350800en_US
dc.contributor.authorid6505876050en_US
dc.date.accessioned2023-05-16T02:48:04Z
dc.date.available2023-05-16T02:48:04Z
dc.date.issued2014
dc.description.abstractThis paper presents a comprehensive investigation of the Self Organizing Map (SOM) classification process of good and defective power distribution transformers. Three main features were extracted from the numerical calculation method of the Sweep Frequency Response Analysis (SFRA) signals acquired from the transformers. These features are the input vectors for the SOM classification. Analysis of the results has shown the capability of the features and the SOM classification method to differentiate between good and defective transformers. © 2014 Penerbit UTM Press. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11113/jt.v67.2762
dc.identifier.epage42
dc.identifier.issue3
dc.identifier.scopus2-s2.0-84896979387
dc.identifier.spage37
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84896979387&doi=10.11113%2fjt.v67.2762&partnerID=40&md5=716ac67aad0c2023b9a2c4723fba2ec4
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22171
dc.identifier.volume67
dc.publisherPenerbit UTM Pressen_US
dc.sourceScopus
dc.sourcetitleJurnal Teknologi (Sciences and Engineering)
dc.titleFeature analysis of numerical calculated data from sweep frequency analysis (SFRA) traces using Self organizing mapsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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