Rolling mill fault diagnosis under limited datasets

Author:

He JunjieORCID,Shi PeimingORCID,Xu Xuefang,Han Dongying

Funder

Natural Science Foundation of Hebei Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference48 articles.

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

2. Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain;Xiao;IEEE/ASME Transact. Mechat.,2022

3. Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises;Yan;Robot. Comput. Integr. Manuf.,2023

4. Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning;Xia;Reliab. Eng. Syst. Saf.,2021

5. Intelligent fault diagnosis of rolling bearing based on wavelet transform and improved resnet under noisy labels and environment;Liang;Eng. Appl. Artif. Intell.,2022

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