Enhanced generative adversarial networks for fault diagnosis of rotating machinery with imbalanced data

Deep learning-based methods have attracted the attention of researchers due to their outstanding performance in automatic feature learning, a crucial step for satisfactory fault diagnosis. However, faults in rotating machinery may occur occasionally, and fault-related signals are difficult to collec...

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Veröffentlicht in:	Measurement science & technology 2019-11, Vol.30 (11), p.115005
Hauptverfasser:	Li, Qi, Chen, Liang, Shen, Changqing, Yang, Bingru, Zhu, Zhongkui
Format:	Artikel
Sprache:	eng
Schlagworte:	deep learning enhanced generative adversarial networks imbalanced data fault diagnosis rotating machinery
Online-Zugang:	Volltext
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