Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice

Citations

Cited by:

1. Zheng, Rui & Najafi, Seyedvahid & Zhang, Yingzhi, 2022. "A recursive method for the health assessment of systems using the proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
2. Huang, Wei & Shao, Changzheng & Hu, Bo & Li, Weizhan & Sun, Yue & Xie, Kaigui & Zio, Enrico & Li, Wenyuan, 2023. "A restoration-clustering-decomposition learning framework for aging-related failure rate estimation of distribution transformers," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
3. Li, Naipeng & Wang, Mingyang & Lei, Yaguo & Si, Xiaosheng & Yang, Bin & Li, Xiang, 2024. "A nonparametric degradation modeling method for remaining useful life prediction with fragment data," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
4. Varbella, Anna & Gjorgiev, Blazhe & Sansavini, Giovanni, 2023. "Geometric deep learning for online prediction of cascading failures in power grids," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
5. Yang, Chen & Xia, Yuanqing, 2024. "Interval Pareto front-based multi-objective robust optimization for sensor placement in structural modal identification," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
6. Liang, Tao & Wang, Fuli & Wang, Shu & Li, Kang & Mo, Xuelei & Lu, Di, 2024. "Machinery health prognostic with uncertainty for mineral processing using TSC-TimeGAN," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
7. Ding, Wenzhe & Bai, Xiang & Wang, Qingwei & Long, Fang & Li, Hailin & Wu, Zhengrong & Liu, Jian & Yao, Huisheng & Yang, Hong, 2024. "A truncated test scheme design method for success-failure in-orbit tests," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
8. Zheng, Minglei & Man, Junfeng & Wang, Dian & Chen, Yanan & Li, Qianqian & Liu, Yong, 2023. "Semi-supervised multivariate time series anomaly detection for wind turbines using generator SCADA data," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
9. Hao, Zhaojun & Di Maio, Francesco & Zio, Enrico, 2023. "A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
10. Zhou, Liang & Wang, Huawei, 2024. "An adaptive multi-scale feature fusion and adaptive mixture-of-experts multi-task model for industrial equipment health status assessment and remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
11. Chen, Zhen & Zhou, Di & Zio, Enrico & Xia, Tangbin & Pan, Ershun, 2023. "Adaptive transfer learning for multimode process monitoring and unsupervised anomaly detection in steam turbines," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
12. Men, Tianli & Li, Yan-Fu & Ji, Yujun & Zhang, Xinliang & Liu, Pengfei, 2022. "Health assessment of high-speed train wheels based on group-profile data," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
13. Sun, Quan & Peng, Fei & Yu, Xianghai & Li, Hongsheng, 2023. "Data augmentation strategy for power inverter fault diagnosis based on wasserstein distance and auxiliary classification generative adversarial network," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
14. Mingfei Li & Jiajian Wu & Zhengpeng Chen & Jiangbo Dong & Zhiping Peng & Kai Xiong & Mumin Rao & Chuangting Chen & Xi Li, 2022. "Data-Driven Voltage Prognostic for Solid Oxide Fuel Cell System Based on Deep Learning," Energies, MDPI, vol. 15(17), pages 1-20, August.
15. Zhou, Taotao & Han, Te & Droguett, Enrique Lopez, 2022. "Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
16. Mukhopadhyay, Koushiki & Liu, Bin & Bedford, Tim & Finkelstein, Maxim, 2023. "Remaining lifetime of degrading systems continuously monitored by degrading sensors," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
17. Li, Xiao Yan & Cheng, De Jun & Fang, Xi Feng & Zhang, Chun Yan & Wang, Yu Feng, 2024. "A novel data augmentation strategy for aeroengine multitask prognosis based on degradation behavior extrapolation and diversity-usability trade-off," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
18. Gjorgiev, Blazhe & Das, Laya & Merkel, Seline & Rohrer, Martina & Auger, Etienne & Sansavini, Giovanni, 2023. "Simulation-driven deep learning for locating faulty insulators in a power line," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
19. 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).
20. Hachem, Hassan & Vu, Hai Canh & Fouladirad, Mitra, 2024. "Different methods for RUL prediction considering sensor degradation," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
21. Wang, Han & Liao, Haitao & Ma, Xiaobing, 2022. "Stochastic Multi-phase Modeling and Health Assessment for Systems Based on Degradation Branching Processes," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
22. Han, Te & Li, Yan-Fu, 2022. "Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
23. Kong, Ziqian & Jin, Xiaohang & Xu, Zhengguo & Chen, Zian, 2023. "A contrastive learning framework enhanced by unlabeled samples for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
24. Wang, Yilin & Li, Yuanxiang & Zhang, Yuxuan & Lei, Jia & Yu, Yifei & Zhang, Tongtong & Yang, Yongshen & Zhao, Honghua, 2024. "Incorporating prior knowledge into self-supervised representation learning for long PHM signal," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
25. Ma, Chenyang & Li, Yongbo & Wang, Xianzhi & Cai, Zhiqiang, 2023. "Early fault diagnosis of rotating machinery based on composite zoom permutation entropy," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
26. Tian, Jilun & Jiang, Yuchen & Zhang, Jiusi & Luo, Hao & Yin, Shen, 2024. "A novel data augmentation approach to fault diagnosis with class-imbalance problem," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
27. Zheng, Shuwen & Wang, Chong & Zio, Enrico & Liu, Jie, 2024. "Fault detection in complex mechatronic systems by a hierarchical graph convolution attention network based on causal paths," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
28. Chen, Xi & Wang, Hui & Lu, Siliang & Xu, Jiawen & Yan, Ruqiang, 2023. "Remaining useful life prediction of turbofan engine using global health degradation representation in federated learning," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
29. Hamed Sadegh Kouhestani & Xiaoping Yi & Guoqing Qi & Xunliang Liu & Ruimin Wang & Yang Gao & Xiao Yu & Lin Liu, 2022. "Prognosis and Health Management (PHM) of Solid-State Batteries: Perspectives, Challenges, and Opportunities," Energies, MDPI, vol. 15(18), pages 1-26, September.
30. 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).
31. 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).
32. Kristjanpoller, Fredy & Cárdenas-Pantoja, Nicolás & Viveros, Pablo & Pascual, Rodrigo, 2023. "Wind farm life cycle cost modelling based on oversizing capacity under load sharing configuration," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
33. Zaitseva, Elena & Levashenko, Vitaly & Rabcan, Jan, 2023. "A new method for analysis of Multi-State systems based on Multi-valued decision diagram under epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
34. Chen, Rentong & Zhang, Chao & Wang, Shaoping & Zio, Enrico & Dui, Hongyan & Zhang, Yadong, 2023. "Importance measures for critical components in complex system based on Copula Hierarchical Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
35. Zhou, Haoxuan & Wang, Bingsen & Zio, Enrico & Wen, Guangrui & Liu, Zimin & Su, Yu & Chen, Xuefeng, 2023. "Hybrid system response model for condition monitoring of bearings under time-varying operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
36. Mao, Wentao & Zhang, Wen & Feng, Ke & Beer, Michael & 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, Elsevier, vol. 242(C).
37. Kamei, Sayaka & Taghipour, Sharareh, 2023. "A comparison study of centralized and decentralized federated learning approaches utilizing the transformer architecture for estimating remaining useful life," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
38. Li, Yang & Gao, Haifeng & Chen, Hongtian & Liu, Chun & Yang, Zhe & Zio, Enrico, 2024. "Accelerated degradation testing for lifetime analysis considering random effects and the influence of stress and measurement errors," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
39. Huang, Zhifu & Yang, Yang & Hu, Yawei & Ding, Xiang & Li, Xuanlin & Liu, Yongbin, 2023. "Attention-augmented recalibrated and compensatory network for machine remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
40. Hu, Changhua & Xing, Yuanxing & Du, Dangbo & Si, Xiaosheng & Zhang, Jianxun, 2023. "Remaining useful life estimation for two-phase nonlinear degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
41. Mandelli, Diego & Wang, Congjian & Agarwal, Vivek & Lin, Linyu & Manjunatha, Koushik A., 2024. "Reliability modeling in a predictive maintenance context: A margin-based approach," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
42. Pang, Zhenan & Li, Tianmei & Pei, Hong & Si, Xiaosheng, 2023. "A condition-based prognostic approach for age- and state-dependent partially observable nonlinear degrading system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
43. Meng, Huixing & Liu, Xuan & Xing, Jinduo & Zio, Enrico, 2022. "A method for economic evaluation of predictive maintenance technologies by integrating system dynamics and evolutionary game modelling," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
44. Xu, Yanwen & Kohtz, Sara & Boakye, Jessica & Gardoni, Paolo & Wang, Pingfeng, 2023. "Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
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61. Compare, Michele & Antonello, Federico & Pinciroli, Luca & Zio, Enrico, 2022. "A general model for life-cycle cost analysis of Condition-Based Maintenance enabled by PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
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