dc.contributor.author | Hemmer, Martin | |
dc.contributor.author | Klausen, Andreas | |
dc.contributor.author | Huynh, Khang | |
dc.contributor.author | Robbersmyr, Kjell Gunnar | |
dc.contributor.author | Waag, Tor Inge | |
dc.date.accessioned | 2020-03-25T10:26:05Z | |
dc.date.available | 2020-03-25T10:26:05Z | |
dc.date.created | 2020-01-23T14:50:33Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Hemmer, 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/Sp11 | en_US |
dc.identifier.issn | 2153-2648 | |
dc.identifier.uri | https://hdl.handle.net/11250/2648526 | |
dc.language.iso | eng | en_US |
dc.publisher | Prognostics and Health Management Society | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Simulation-driven Deep Classification of Bearing Faults from Raw Vibration Data | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | © 2019 The Author(s) | en_US |
dc.subject.nsi | VDP::Teknologi: 500 | en_US |
dc.source.pagenumber | 12 | en_US |
dc.source.volume | 10 | en_US |
dc.source.journal | International Journal of Prognostics and Health Management | en_US |
dc.source.issue | Special Issue on Deep Learning and Emerging Analytics | en_US |
dc.identifier.cristin | 1780978 | |
dc.source.articlenumber | 030 | |
cristin.qualitycode | 1 | |