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A neural network-based tool for magnetic performance prediction of toroidal cores

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dc.contributor.authorMiti, G.K.
dc.contributor.authorMoses, Anthony John
dc.contributor.authorFox, David
dc.contributor.buuauthorDerebaşı, Naim
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Bölümü
dc.contributor.scopusid11540936300
dc.date.accessioned2022-03-23T07:19:11Z
dc.date.available2022-03-23T07:19:11Z
dc.date.issued2003-01
dc.descriptionBu çalışma, 05-07 Eylül 2001 tarihleri arasında Bilbao[İspanya]’da düzenlenen 15. International Symposium on Soft Magnetic Materials’da bildiri olarak sunulmuştur.
dc.description.abstractGeometrical and building parameters have a strong influence on magnetic performance of wound toroidal cores made from electrical steel or similar strip products. This paper presents a neural network-based approach to predict losses and permeability in such cores of varying geometries over an induction range of 0.2-1.8T (50Hz). The approach is shown to be successful.
dc.description.sponsorshipMCYT, Gobierno Espanol
dc.description.sponsorshipEngineering and Physical Sciences Research Council GR/L36093/01
dc.description.sponsorshipUniv Investigac, Dept Educ
dc.description.sponsorshipUniv Paris Vasco, Euskal Herriko Unibertsitatea
dc.description.sponsorshipReal Soc Bascongada Amigos Pais
dc.description.sponsorshipAgilent Technologies
dc.description.sponsorshipBFI, Optilas
dc.identifier.citationMiti, G. K. vd. (2003). “A neural network-based tool for magnetic performance prediction of toroidal cores”. Journal of Magnetism and Magnetic Materials, 254(Special Issue), 262-264.
dc.identifier.doi10.1016/S0304-8853(02)00788-6
dc.identifier.endpage264
dc.identifier.issn0304-8853
dc.identifier.issueSpecial Issue
dc.identifier.scopus2-s2.0-0037211428
dc.identifier.startpage262
dc.identifier.urihttps://doi.org/10.1016/S0304-8853(02)00788-6
dc.identifier.urihttp://hdl.handle.net/11452/25292
dc.identifier.volume254
dc.identifier.wos000180075600081
dc.indexed.wosSCIE
dc.indexed.wosCPCIS
dc.language.isoen
dc.publisherElsevier
dc.relation.collaborationYurt dışı
dc.relation.journalJournal of Magnetism and Magnetic Materials
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMaterials science
dc.subjectPhysics
dc.subjectArtificial intelligence
dc.subjectMagnetic losses
dc.subjectNeural networks
dc.subjectSoft magnetic materials
dc.subjectStrip-wound cores
dc.subjectMagnetic leakage
dc.subjectMagnetic permeability
dc.subjectToroidal cores
dc.subjectMagnetic cores
dc.subject.scopusSilicon Steel; Soft Magnetic Materials; Iron
dc.subject.wosMaterials science, multidisciplinary
dc.subject.wosPhysics, condensed matter
dc.titleA neural network-based tool for magnetic performance prediction of toroidal cores
dc.typeconferenceObject
dc.type.subtypeProceedings Paper
dc.wos.quartileQ2 (Materials science, multidisciplinary)
dc.wos.quartileQ3 (Physics, condensed matter)
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Bölümü
local.indexed.atScopus
local.indexed.atWOS

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