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1 Ergebnisse
1
SIMULATION-DRIVEN DEEP CLASSIFICATION OF BEARING FAULTS FRO..:
Martin Hemmer
;
Andreas Klausen
;
Huynh van Khang
..
https://doaj.org/toc/2153-2648. , 2019
Link:
https://doi.org/10.36001/ijphm.2019.v10i4.2615
RT Journal T1
SIMULATION-DRIVEN DEEP CLASSIFICATION OF BEARING FAULTS FROM RAW VIBRATION DATA
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:3fef6f70aed44662877fad24279fe13b&Exemplar=1&LAN=DE A1 Martin Hemmer A1 Andreas Klausen A1 Huynh van Khang A1 Kjell G. Robbersmyr A1 Tor I. Waag PB The Prognostics and Health Management Society YR 2019 K1 convolutional neural network K1 bearing fault diagnosis K1 deep learning for time-series K1 Engineering machinery K1 tools K1 and implements K1 TA213-215 K1 Systems engineering K1 TA168 JF https://doaj.org/toc/2153-2648 LK http://dx.doi.org/https://doi.org/10.36001/ijphm.2019.v10i4.2615 DO https://doi.org/10.36001/ijphm.2019.v10i4.2615 SF ELIB - SuUB Bremen
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