Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework

Citations

Cited by:

1. Tohme, Tony & Vanslette, Kevin & Youcef-Toumi, Kamal, 2023. "Reliable neural networks for regression uncertainty estimation," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
2. Xue, Gang & Liu, Shifeng & Ren, Long & Gong, Daqing, 2024. "Risk assessment of utility tunnels through risk interaction-based deep learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
3. Wang, Jian & Liu, Huiyuan & Gao, Shibin & Yu, Long & Liu, Xingyang & Zhang, Dongkai & Kou, Lei, 2024. "Robust deep Gaussian process-based trustworthy fog-haze-caused pollution flashover prediction approach for overhead contact lines," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
4. Floreale, Giovanni & Baraldi, Piero & Lu, Xuefei & Rossetti, Paolo & Zio, Enrico, 2024. "Sensitivity analysis by differential importance measure for unsupervised fault diagnostics," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
5. Rombach, Katharina & Michau, Gabriel & Fink, Olga, 2023. "Controlled generation of unseen faults for Partial and Open-Partial domain adaptation," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
6. Feng, Tingting & Li, Shichao & Guo, Liang & Gao, Hongli & Chen, Tao & Yu, Yaoxiang, 2023. "A degradation-shock dependent competing failure processes based method for remaining useful life prediction of drill bit considering time-shifting sudden failure threshold," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
7. Zhao, Chao & Shen, Weiming, 2022. "Adaptive open set domain generalization network: Learning to diagnose unknown faults under unknown working conditions," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
8. Zhang, Guowei & Kong, Xianguang & Wang, Qibin & Du, Jingli & Wang, Jinrui & Ma, Hongbo, 2024. "Single domain generalization method based on anti-causal learning for rotating machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
9. Zhou, Taotao & Zhang, Laibin & Han, Te & Droguett, Enrique Lopez & Mosleh, Ali & Chan, Felix T.S., 2023. "An uncertainty-informed framework for trustworthy fault diagnosis in safety-critical applications," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
10. Aizpurua, J.I. & Stewart, B.G. & McArthur, S.D.J. & Penalba, M. & Barrenetxea, M. & Muxika, E. & Ringwood, J.V., 2022. "Probabilistic forecasting informed failure prognostics framework for improved RUL prediction under uncertainty: A transformer case study," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
11. Zhang, Xingwu & Zhao, Yu & Yu, Xiaolei & Ma, Rui & Wang, Chenxi & Chen, Xuefeng, 2023. "Weighted domain separation based open set fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
12. Zheng, Shuwen & Pan, Kai & Liu, Jie & Chen, Yunxia, 2024. "Empirical study on fine-tuning pre-trained large language models for fault diagnosis of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
13. Yu, Xiaolei & Zhao, Zhibin & Zhang, Xingwu & Chen, Xuefeng & Cai, Jianbing, 2023. "Statistical identification guided open-set domain adaptation in fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
14. Zhou, Taotao & Zhang, Xiaoge & Droguett, Enrique Lopez & Mosleh, Ali, 2023. "A generic physics-informed neural network-based framework for reliability assessment of multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
15. Yue, Ke & Li, Jipu & Deng, Shuhan & Kwoh, Chee Keong & Chen, Zhuyun & Li, Weihua, 2024. "A relationship-aware calibrated prototypical network for fault incremental diagnosis of electric motors without reserved samples," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
16. Zhou, Chengyu & Fang, Xiaolei, 2023. "A convex two-dimensional variable selection method for the root-cause diagnostics of product defects," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
17. Wang, Jian & Gao, Shibin & Yu, Long & Liu, Xingyang & Neri, Ferrante & Zhang, Dongkai & Kou, Lei, 2024. "Uncertainty-aware trustworthy weather-driven failure risk predictor for overhead contact lines," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
18. Yuan, Zixia & Xiong, Guojiang & Fu, Xiaofan & Mohamed, Ali Wagdy, 2023. "Improving fault tolerance in diagnosing power system failures with optimal hierarchical extreme learning machine," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
19. Pan, Junlin & Sun, Bo & Wu, Zeyu & Yi, Zechen & Feng, Qiang & Ren, Yi & Wang, Zili, 2024. "Probabilistic remaining useful life prediction without lifetime labels: A Bayesian deep learning and stochastic process fusion method," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
20. Yang, Zhen & Dong, Xiaobin & Guo, Li, 2023. "Scenario inference model of urban metro system cascading failure under extreme rainfall conditions," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
21. Zhang, Wei & Wang, Ziwei & Li, Xiang, 2023. "Blockchain-based decentralized federated transfer learning methodology for collaborative machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
22. Wang, Jian & Gao, Shibin & Yu, Long & Zhang, Dongkai & Xie, Chenlin & Chen, Ke & Kou, Lei, 2023. "Data-driven lightning-related failure risk prediction of overhead contact lines based on Bayesian network with spatiotemporal fragility model," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
23. Xu, Jinjin & Wang, Rongxi & Liang, Zeming & Liu, Pengpeng & Gao, Jianmin & Wang, Zhen, 2023. "Physics-guided, data-refined fault root cause tracing framework for complex electromechanical system," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
24. Zhu, Zuanyu & Cheng, Junsheng & Wang, Ping & Wang, Jian & Kang, Xin & Yang, Yu, 2023. "A novel fault diagnosis framework for rotating machinery with hierarchical multiscale symbolic diversity entropy and robust twin hyperdisk-based tensor machine," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
25. 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).
26. Dai, Menghang & Liu, Zhiliang & Wang, Jinrui & Zuo, Mingjian, 2024. "Physics-driven feature alignment combined with dynamic distribution adaptation for three-cylinder drilling pump cross-speed fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
27. Zhao, Zeyun & Wang, Jia & Tao, Qian & Li, Andong & Chen, Yiyang, 2024. "An unknown wafer surface defect detection approach based on Incremental Learning for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 244(C).