Automatic feature extraction of time-series applied to fault severity assessment of helical gearbox in stationary and non-stationary speed operation

[Display omitted] •An automatic feature extraction method is proposed.•Manual feature extraction procedures can be replaced with deep learning approach.•Valid features can be extracted from a time-frequency representation of time-series.•A pre-trained layer by layer model is better than a model with...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Applied soft computing Jg. 58; S. 53 - 64
Hauptverfasser:	Cabrera, Diego, Sancho, Fernando, Li, Chuan, Cerrada, Mariela, Sánchez, René-Vinicio, Pacheco, Fannia, de Oliveira, José Valente
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.09.2017
Schlagworte:	Auto-encoder Convolution Deep learning Helical gearbox Wavelet packets Deep learning Wavelet packets Helical gearbox Convolution Auto-encoder
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!