Bearing fault diagnosis with envelope analysis and machine Learning approaches using CWRU dataset

dc.contributor.author	Alonso González, Miguel Ángel
dc.contributor.author	García Díaz, Vicente
dc.contributor.author	López Pérez, Benjamín
dc.contributor.author	Pelayo García-Bustelo, Begoña Cristina
dc.contributor.author	Anzola, J. P.
dc.date.accessioned	2023-10-25T08:54:32Z
dc.date.available	2023-10-25T08:54:32Z
dc.date.issued	2023
dc.identifier.citation	IEEE Access, 11, p. 57796-57805 (2023); doi:10.1109/Access.2023.3283466
dc.identifier.issn	2169-3536
dc.identifier.uri	https://hdl.handle.net/10651/69892
dc.description.sponsorship	Los Libertadores University Foundation [ING-21-22]; Computer Science Department of the University of Oviedo
dc.format.extent	p. 57796-57805
dc.language.iso	eng
dc.relation.ispartof	IEEE Access
dc.rights	© Los autores
dc.rights	CC Reconocimiento - No Comercial - Sin Obra Derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161608424&doi=10.1109%2fAccess.2023.3283466&partnerID=40&md5=dd39ffb040dbc08bacc50ea0b196c073
dc.title	Bearing fault diagnosis with envelope analysis and machine Learning approaches using CWRU dataset
dc.type	journal article
dc.identifier.doi	10.1109/Access.2023.3283466
dc.relation.publisherversion	http://dx.doi.org/10.1109/Access.2023.3283466
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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