Deep temporal–spectral domain adaptation for bearing fault diagnosis

Author:

Ding YifeiORCID,Cao Yudong,Jia Minping,Ding Peng,Zhao Xiaoli,Lee Chi-GuhnORCID

Publisher

Elsevier BV

Reference40 articles.

1. Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain;Xiao;IEEE/ASME Trans. Mechatronics,2022

2. Dual-threshold attention-guided gan and limited infrared thermal images for rotating machinery fault diagnosis under speed fluctuation;Shao;IEEE Trans. Ind. Inform.,2023

3. Multiscale inverted residual convolutional neural network for intelligent diagnosis of bearings under variable load condition;Zhao;Measurement,2022

4. Bearing fault diagnosis method based on adaptive maximum cyclostationarity blind deconvolution;Wang;Mech. Syst. Signal Process.,2022

5. Machinery fault diagnosis with imbalanced data using deep generative adversarial networks;Zhang;Measurement,2020

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