Health indicator for machine condition monitoring built in the latent space of a deep autoencoder

dc.contributor.author	González Muñiz, Ana
dc.contributor.author	Díaz Blanco, Ignacio
dc.contributor.author	Cuadrado Vega, Abel Alberto
dc.contributor.author	García Pérez, Diego
dc.date.accessioned	2022-11-08T12:44:18Z
dc.date.available	2022-11-08T12:44:18Z
dc.date.issued	2022
dc.identifier.citation	Reliability Engineering and System Safety, 224, (2022); doi:10.1016/j.ress.2022.108482
dc.identifier.issn	0951-8320
dc.identifier.uri	http://hdl.handle.net/10651/65555
dc.description.sponsorship	Spanish National Research Agency [PID2020-115401GB-I00/AEI/10.13039/501100011033]; Principado de Asturias regional government
dc.language.iso	eng
dc.relation.ispartof	Reliability Engineering and System Safety
dc.rights	© 2022 The authors. Published by Elsevier Ltd.
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-s2.0-85129508290&doi=10.1016%2fj.ress.2022.108482&partnerID=40&md5=9a8182f7bc6d0a383a8f2c2da7d71eb0
dc.title	Health indicator for machine condition monitoring built in the latent space of a deep autoencoder
dc.type	journal article
dc.identifier.doi	10.1016/j.ress.2022.108482
dc.local.notes	OA ATUO22
dc.relation.projectID	AEI/PID2020-115401GB-I00
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.ress.2022.108482
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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