 | Up a level |
Feng, Ke, Ji, JC, Zhang, Yongchao, Ni, Qing, Liu, Zheng and Beer, Michael 
ORCID: 0000-0002-0611-0345
(2023)
Digital twin-driven intelligent assessment of gear surface degradation.
Mechanical Systems and Signal Processing, 186.
p. 109896.
Mao, Wentao, Zhang, Wen, Feng, Ke, Beer, Michael ORCID: 0000-0002-0611-0345 and Yang, Chunsheng
(2024)
Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines.
Reliability Engineering and System Safety, 242.
p. 109695.
Zhang, Yongchao, Ren, Zhaohui, Feng, Ke, Yu, Kun, Beer, Michael ORCID: 0000-0002-0611-0345 and Liu, Zheng
(2023)
Universal source-free domain adaptation method for cross-domain fault diagnosis of machines.
Mechanical Systems and Signal Processing, 191.
p. 110159.
Xu, Yadong, Ji, JC, Ni, Qing, Feng, Ke, Beer, Michael ORCID: 0000-0002-0611-0345 and Chen, Hongtian
(2023)
A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems.
Mechanical Systems and Signal Processing, 200.
p. 110609.
Feng, Ke, Ni, Qing, Beer, Michael ORCID: 0000-0002-0611-0345, Du, Haiping and Li, Chuan
(2022)
A novel similarity-based status characterization methodology for gear surface wear propagation monitoring.
TRIBOLOGY INTERNATIONAL, 174.
p. 107765.
Feng, Ke, Ji, JC, Ni, Qing and Beer, Michael ORCID: 0000-0002-0611-0345
(2023)
A review of vibration-based gear wear monitoring and prediction techniques.
Mechanical Systems and Signal Processing, 182.
p. 109605.