A PATTERN RECOGNITION APPROACH FOR CLASSIFICATION OF POWER QUALITY DISTURBANCE TYPES

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dc.authoridUYAR, Murat/0000-0001-7243-7939
dc.contributor.authorUyar, Murat
dc.contributor.authorYildirim, Selcuk
dc.contributor.authorGencoglu, Muhsin Tunay
dc.date.accessioned2024-12-24T19:33:16Z
dc.date.available2024-12-24T19:33:16Z
dc.date.issued2011
dc.departmentSiirt Üniversitesi
dc.description.abstractIn this study, an algorithm based on pattern recognition approach is proposed for classification of power quality disturbance types. For feature extraction which is an important part of the pattern recognition, a method based on entropy which uses the decomposition coefficients of wavelet transform is presented. The most important advantage of the method is the reduction of data size without losing main distinguishing characteristics of signal. Support vector machines based on statistical learning theory is used as a classifier. The performance of the proposed algorithm is evaluated by using real and synthetic power quality disturbance data. Real power quality disturbance data are obtained from our national power system. Besides, the synthetic power quality disturbance data are obtained from ATP/EMTP and mathematical models. The analyses and results obtained in this study show that proposed algorithm has an efficient, feasible and practical structure.
dc.identifier.endpage56
dc.identifier.issn1300-1884
dc.identifier.issn1304-4915
dc.identifier.issue1
dc.identifier.startpage41
dc.identifier.urihttps://hdl.handle.net/20.500.12604/8026
dc.identifier.volume26
dc.identifier.wosWOS:000289174900005
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherGazi Univ, Fac Engineering Architecture
dc.relation.ispartofJournal of The Faculty of Engineering and Architecture of Gazi University
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectPattern recognition
dc.subjectpower quality disturbances
dc.subjectwavelet transform
dc.subjectsupport vector machines
dc.titleA PATTERN RECOGNITION APPROACH FOR CLASSIFICATION OF POWER QUALITY DISTURBANCE TYPES
dc.typeArticle

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