Autoencoder-based representation learning and its application in intelligent fault diagnosis: A review

With the increase of the scale and complexity of mechanical equipment, traditional intelligent fault diagnosis (IFD) based on shallow machine learning methods is unable to meet the demand of coupling faults. In the past decades, the vigorous development of deep learning (DL) brings new opportunities...

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Bibliographic Details
Published in:	Measurement : journal of the International Measurement Confederation Vol. 189; p. 110460
Main Authors:	Yang, Zheng, Xu, Binbin, Luo, Wei, Chen, Fei
Format:	Journal Article
Language:	English
Published:	London Elsevier Ltd 15.02.2022 Elsevier Science Ltd
Subjects:	Application Autoencoder Complexity Deep learning Fault diagnosis Intelligent fault diagnosis Intelligent systems Machine learning Mathematical models Optimization Representation learning Representations Representation learning Intelligent fault diagnosis Autoencoder Application Optimization
ISSN:	0263-2241, 1873-412X
Online Access:	Get full text
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