Publication:
A Novel Transformer Protection Method Based on Hilbert Huang Transform and Artificial Neural Network

dc.authorscopusid22433630600
dc.authorscopusid35791875600
dc.contributor.authorÖzgönenel, O.
dc.contributor.authorKaragöl, S.
dc.date.accessioned2020-06-21T14:16:30Z
dc.date.available2020-06-21T14:16:30Z
dc.date.issued2013
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Özgönenel] Okan, Department of Electrical and Electronic Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Karagöl] Serap, Department of Electrical and Electronic Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractThis paper presents the application of Hilbert-Huang Transform (HHT) and artificial neural network (ANN) for fault detection on transformers. The combined procedure, Emprical mode decomposition (EMD) and Hilbert transform, is called the Hilbert-Huang Transform (HHT). The ANN is designed and trained using feed forward propagation algorithm. The input features of the ANN are extracted from the frequency and aplitude of IMFs by applying the Hilbert transform. Simulation results of the proposed method for fault detection on tranformers proveto be effective. © 2013 The Chamber of Turkish Electrical Engineers-Bursa.en_US
dc.identifier.doi10.1109/eleco.2013.6713836
dc.identifier.endpage228en_US
dc.identifier.isbn9786050105049
dc.identifier.scopus2-s2.0-84894164022
dc.identifier.startpage225en_US
dc.identifier.urihttps://doi.org/10.1109/eleco.2013.6713836
dc.identifier.wosWOS:000333752200047
dc.language.isoenen_US
dc.publisherIEEE Computer Society help@computer.orgen_US
dc.relation.ispartof-- 8th International Conference on Electrical and Electronics Engineering, ELECO 2013en_US
dc.relation.journal2013 8Th International Conference on Electrical and Electronics Engineering (Eleco)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleA Novel Transformer Protection Method Based on Hilbert Huang Transform and Artificial Neural Networken_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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