Simple record

dc.rights.licenseAttribution 4.0 International*
dc.contributor.authorGonzalez-Jimenez, David
dc.contributor.authordel-Olmo, Jon
dc.contributor.authorPoza, Javier
dc.contributor.authorGarramiola, Fernando
dc.contributor.authorMadina, Patxi
dc.date.accessioned2021-06-14T10:18:02Z
dc.date.available2021-06-14T10:18:02Z
dc.date.issued2021
dc.identifier.issn1424-8220en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=163782en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/5319
dc.description.abstractThe need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has shifted to massively acquire operational data, which can be processed to extract really valuable information with the help of Machine Learning or Deep Learning techniques. As a result, classical Condition Monitoring methodologies, such as model- and signal-based ones are being overcome by data-driven approaches. Therefore, the current paper provides a review of these data-driven active supervision strategies implemented in electric drives for fault detection and diagnosis (FDD). Hence, first, an overview of the main FDD methods is presented. Then, some basic guidelines to implement the Machine Learning workflow on which most data-driven strategies are based, are explained. In addition, finally, the review of scientific articles related to the topic is provided, together with a discussion which tries to identify the main research gaps and opportunities.en
dc.language.isoengen
dc.publisherMDPIen
dc.rights© 2021 by the authors. Licensee MDPIen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectcondition monitoringen
dc.subjectdata-drivenen
dc.subjectelectric driveen
dc.subjectfault detectionen
dc.subjectelectric tractionen
dc.subjectFault diagnosisen
dc.subjectMachine learningen
dc.titleData-Driven Fault Diagnosis for Electric Drives: A Reviewen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceSensorsen
local.contributor.groupAccionamientos aplicados a la tracción y a la generación de energía eléctricaes
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.3390/s21124024en
local.rights.publicationfeeAPCen
local.rights.publicationfeeamount2020 EURen
local.source.detailsVol. 21. N. 12. N. artículo 4024, 2021en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore
oaire.resourceTypehttp://purl.org/coar/resource_type/c_6501en
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85en


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Simple record

Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International