Yayın:
Power loss modelling on different types of amorphous ribbons

dc.contributor.authorKüçük, İlker
dc.contributor.authorDerebaşı, Naim
dc.contributor.buuauthorKÜÇÜK, İLKER
dc.contributor.buuauthorDEREBAŞI, NAİM
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Bölümü
dc.contributor.scopusid6602910810
dc.contributor.scopusid11540936300
dc.date.accessioned2025-05-13T14:04:54Z
dc.date.issued2007-03-01
dc.description.abstractThis paper presents a new artificial neural network approach based on dynamic Preisach model and finite element method to compute power loss on amorphous ribbons. The power loss values on these ribbons obtained from the finite element method and dynamic Preisach model have been used as a training data in this artificial neural network model. The model is fast, does not require a large set of measurement data and does not require tremendous computational efforts. The results obtained by using the proposed new model are in good agreement with experimental results previously reported. Copyright © 2007 American Scientific Publishers. All rights reserved.
dc.identifier.doi10.1166/sl.2007.061
dc.identifier.endpage247
dc.identifier.issn1546-198X
dc.identifier.issue1
dc.identifier.scopus2-s2.0-34248594270
dc.identifier.startpage244
dc.identifier.urihttps://hdl.handle.net/11452/52737
dc.identifier.volume5
dc.indexed.scopusScopus
dc.language.isoen
dc.relation.journalSensor Letters
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectPower loss
dc.subjectNeural network
dc.subjectFinite element method
dc.subjectAmorphous ribbon
dc.subject.scopusMagnetic Core; Flux Density; Electrical Steel
dc.titlePower loss modelling on different types of amorphous ribbons
dc.typeconferenceObject
dc.type.subtypeConference Paper
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Bölümü
local.indexed.atScopus
relation.isAuthorOfPublicationa349a06c-7ca6-4a27-8708-8157e5962651
relation.isAuthorOfPublication0c85f61f-70fa-4f0d-83a0-a3a0ac50e069
relation.isAuthorOfPublication.latestForDiscoverya349a06c-7ca6-4a27-8708-8157e5962651

Dosyalar