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Simulation-driven Deep Classification of Bearing Faults from Raw Vibration Data

dc.contributor.authorHemmer, Martin
dc.contributor.authorKlausen, Andreas
dc.contributor.authorHuynh, Khang
dc.contributor.authorRobbersmyr, Kjell Gunnar
dc.contributor.authorWaag, Tor Inge
dc.date.accessioned2020-03-25T10:26:05Z
dc.date.available2020-03-25T10:26:05Z
dc.date.created2020-01-23T14:50:33Z
dc.date.issued2019
dc.identifier.citationHemmer, M., Klausen, A., Huynh, K., Robbersmyr, K. G. & Waag, T. I. (2019). Simulation-driven Deep Classification of Bearing Faults from Raw Vibration Data. International Journal of Prognostics and Health Management, 10(Special Issue on Deep Learning and Emerging Analytics): 030. Retrieved from http://www.phmsociety.org/references/ijphm-archives/2019/Sp11en_US
dc.identifier.issn2153-2648
dc.identifier.urihttps://hdl.handle.net/11250/2648526
dc.language.isoengen_US
dc.publisherPrognostics and Health Management Societyen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleSimulation-driven Deep Classification of Bearing Faults from Raw Vibration Dataen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2019 The Author(s)en_US
dc.subject.nsiVDP::Teknologi: 500en_US
dc.source.pagenumber12en_US
dc.source.volume10en_US
dc.source.journalInternational Journal of Prognostics and Health Managementen_US
dc.source.issueSpecial Issue on Deep Learning and Emerging Analyticsen_US
dc.identifier.cristin1780978
dc.source.articlenumber030
cristin.qualitycode1


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