Semi-supervised ensemble fault diagnosis method based on adversarial decoupled auto-encoder with extremely limited labels
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DOI: 10.1016/j.ress.2023.109740
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- Xia, Pengcheng & Huang, Yixiang & Tao, Zhiyu & Liu, Chengliang & Liu, Jie, 2023. "A digital twin-enhanced semi-supervised framework for motor fault diagnosis based on phase-contrastive current dot pattern," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Yao, Jiachi & Han, Te, 2023. "Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data," Energy, Elsevier, vol. 271(C).
- Li, Xin & Li, Yong & Yan, Ke & Shao, Haidong & (Jing) Lin, Janet, 2023. "Intelligent fault diagnosis of bevel gearboxes using semi-supervised probability support matrix machine and infrared imaging," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Wang, Jinrui & Zhang, Zongzhen & Liu, Zhiliang & Han, Baokun & Bao, Huaiqian & Ji, Shanshan, 2023. "Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Zhang, Yongchao & Ji, J.C. & Ren, Zhaohui & Ni, Qing & Gu, Fengshou & Feng, Ke & Yu, Kun & Ge, Jian & Lei, Zihao & Liu, Zheng, 2023. "Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Liu, Junqiang & Pan, Chunlu & Lei, Fan & Hu, Dongbin & Zuo, Hongfu, 2021. "Fault prediction of bearings based on LSTM and statistical process analysis," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
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- Wu, Zhangjun & Xu, Renli & Luo, Yuansheng & Shao, Haidong, 2024. "A holistic semi-supervised method for imbalanced fault diagnosis of rotational machinery with out-of-distribution samples," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
- Liu, Ruonan & Zhang, Quanhu & Lin, Di & Zhang, Weidong & Ding, Steven X., 2024. "Causal intervention graph neural network for fault diagnosis of complex industrial processes," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
- Fu, Xingchen & Jiao, Keming & Tao, Jianfeng & Liu, Chengliang, 2024. "Multi-stream domain adversarial prototype network for integrated smart roller TBM main bearing fault diagnosis across various low rotating speeds," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
- Li, Ying & Zhang, Lijie & Liang, Pengfei & Wang, Xiangfeng & Wang, Bin & Xu, Leitao, 2024. "Semi-supervised meta-path space extended graph convolution network for intelligent fault diagnosis of rotating machinery under time-varying speeds," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
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Keywords
Adversarial decoupled auto-encoder; Distance metric; Extremely limited labels; Semi-supervised;All these keywords.
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