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

dc.contributor.authorsOzgonenel O., Terzi U.K., Akar O., Kurt U.
dc.date.accessioned2022-03-15T02:14:01Z
dc.date.accessioned2026-01-11T14:32:34Z
dc.date.available2022-03-15T02:14:01Z
dc.date.issued2019
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.
dc.identifier.doi10.23919/ELECO47770.2019.8990377
dc.identifier.isbn9786050112757
dc.identifier.urihttps://hdl.handle.net/11424/247991
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofELECO 2019 - 11th International Conference on Electrical and Electronics Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial Neural Network
dc.subjectMagnetizing Inrush Current
dc.subjectStockwell Transform
dc.subjectTransformer
dc.titleDiscrimination of Magnetizing Inrush and Internal Fault Currents Based on Stockwell Transform and ANN Approach for Transformer Protection
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage100
oaire.citation.startPage96
oaire.citation.titleELECO 2019 - 11th International Conference on Electrical and Electronics Engineering

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