Deep Transfer Learning Method Based on 1D-CNN for Bearing Fault Diagnosis

Deep Transfer Learning Method Based on 1D-CNN for Bearing Fault Diagnosis

In mechanical fault diagnosis, it is impossible to collect massive labeled samples with the same distribution in real industry. Transfer learning, a promising method, is usually used to address the critical problem. However, as the number of samples increases, the interdomain distribution discrepanc...

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Bibliographic Details
Main Authors:	Jun He, Xiang Li, Yong Chen, Danfeng Chen, Jing Guo, Yan Zhou
Format:	Article
Language:	English
Published:	Wiley 2021-01-01
Series:	Shock and Vibration
Online Access:	http://dx.doi.org/10.1155/2021/6687331
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