Publication:
Discrimination of Magnetizing Inrush and Internal Fault Currents Based on Stockwell Transform and ANN Approach for Transformer Protection

dc.authorscopusid22433630600
dc.authorscopusid35103686000
dc.authorscopusid57215411486
dc.authorscopusid35409580000
dc.contributor.authorÖzgönenel, O.
dc.contributor.authorTerzi, U.K.
dc.contributor.authorAkar, O.
dc.contributor.authorKurt, U.
dc.date.accessioned2020-06-21T09:05:22Z
dc.date.available2020-06-21T09:05:22Z
dc.date.issued2019
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Özgönenel] Okan, Department of Electrical and Electronic Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Terzi] Ümit Kemalettin, Department of Electrical and Electronic Engineering, Marmara Üniversitesi, Istanbul, Turkey; [Akar] Onur, Department of Electronics and Automation, Gedik Üniversitesi, Istanbul, Turkey; [Kurt] Ünal, Faculty of Technology, Amasya Üniversitesi, Amasya, Turkeyen_US
dc.description.abstractIn this study, Stockwell transform and artificial neural network were used in determining the inrush current and the internal current fault based on the power transformer protection. The S-transform is a robust transform that incorporates the time and frequency characteristics used in the analysis of non-stationary short term transient signals. It is used for pattern recognition for distinction between internal faults and inrush current. Time-frequency images were obtained by using S-transform, and the obtained images were observed to be different in internal faults and inrush current. The feature extraction is based on statistical methods, standard deviation and average value, the classification process was performed with the multilayer feed forward artificial neural network. The classification performance is calculated at a hundred percent accuracy. © 2019 Chamber of Turkish Electrical Engineers.en_US
dc.identifier.doi10.23919/ELECO47770.2019.8990377
dc.identifier.endpage100en_US
dc.identifier.isbn9786050112757
dc.identifier.scopus2-s2.0-85080893334
dc.identifier.scopusqualityN/A
dc.identifier.startpage96en_US
dc.identifier.urihttps://doi.org/10.23919/ELECO47770.2019.8990377
dc.identifier.urihttps://hdl.handle.net/20.500.12712/2304
dc.identifier.wosqualityN/A
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof-- 11th International Conference on Electrical and Electronics Engineering, ELECO 2019 -- 2019-11-28 through 2019-11-30 -- Bursa -- 157784en_US
dc.relation.journalELECO 2019 - 11th International Conference on Electrical and Electronics Engineeringen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectMagnetizing Inrush Currenten_US
dc.subjectStockwell Transformen_US
dc.subjectTransformeren_US
dc.titleDiscrimination of Magnetizing Inrush and Internal Fault Currents Based on Stockwell Transform and ANN Approach for Transformer Protectionen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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