Matlab Implementation Of Multilayer Perceptron For Bearing Faults Classification

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but.event.date27.04.2021cs
but.event.titleSTUDENT EEICT 2021cs
dc.contributor.authorDoseděl, Martin
dc.date.accessioned2023-01-06T10:05:43Z
dc.date.available2023-01-06T10:05:43Z
dc.date.issued2021cs
dc.description.abstractThis paper deals with implementation of multilayer perceptron neural network (NN) forbearing faults classification. Neural network has been created from scratch as an M-script with backpropagation learning algorithm also, but without using advanced MATLAB packages. Public availablebearing dataset from CaseWestern Reserve University has been used for both training and testingphase, as well as for the final classification process. Problem with sparse input data for training thenetwork has also been addressed. This relatively simple and small neural network is capable to classifythe failures of a bearing with very low error rate.en
dc.formattextcs
dc.format.extent161-165cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 27st Conference STUDENT EEICT 2021: Selected Papers. s. 161-165. ISBN 978-80-214-5943-4cs
dc.identifier.doi10.13164/eeict.2021.161
dc.identifier.isbn978-80-214-5943-4
dc.identifier.urihttp://hdl.handle.net/11012/200833
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 27st Conference STUDENT EEICT 2021: Selected papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazenics
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectMultilayer perceptron (MLP)en
dc.subjectdeep learningen
dc.subjectdata classificationen
dc.subjectback-propagation algorithm,bearing faultsen
dc.titleMatlab Implementation Of Multilayer Perceptron For Bearing Faults Classificationen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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