Deep Reconstruction Transfer Convolutional Neural Network for Rolling Bearing Fault Diagnosis

Deep Reconstruction Transfer Convolutional Neural Network for Rolling Bearing Fault Diagnosis

Deep transfer learning has been widely used to improve the versatility of models. In the problem of cross-domain fault diagnosis in rolling bearings, most models require that the given data have a similar distribution, which limits the diagnostic effect and generalization of the model. This paper pr...

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Bibliographic Details
Main Authors: Ziwei Feng, Qingbin Tong, Xuedong Jiang, Feiyu Lu, Xin Du, Jianjun Xu, Jingyi Huo
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Sensors
Subjects:
intelligent fault diagnosis
transfer learning
domain adaptation
autoencoder
label smoothing
Online Access:https://www.mdpi.com/1424-8220/24/7/2079

Internet

https://www.mdpi.com/1424-8220/24/7/2079

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