IDEAS home Printed from https://ideas.repec.org/f/c/pha1518.html
   My authors  Follow this author

Te Han Sr.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Yao, Yuantao & Han, Te & Yu, Jie & Xie, Min, 2024. "Uncertainty-aware deep learning for reliable health monitoring in safety-critical energy systems," Energy, Elsevier, vol. 291(C).

    Cited by:

    1. Wang, Haotong & Shi, Jianxin & Lin, Chaojing & Liu, Xinmeng & Li, Guolong & Sun, Shengdi & Zhou, Xin & Li, Yanjun, 2025. "Nuclear power systems unsupervised anomaly localization considering spatiotemporal information and influence mechanism between devices," Energy, Elsevier, vol. 325(C).
    2. Jiasheng Yan & Yang Sui & Tao Dai, 2025. "A Particle Swarm Optimization-Based Ensemble Broad Learning System for Intelligent Fault Diagnosis in Safety-Critical Energy Systems with High-Dimensional Small Samples," Mathematics, MDPI, vol. 13(5), pages 1-21, February.
    3. Cao, Yudong & Zhuang, Jichao & Miao, Qiuhua & Jia, Minping & Feng, Ke & Zhao, Xiaoli & Yan, Xiaoan & Ding, Peng, 2024. "Source-free domain adaptation for transferable remaining useful life prediction of machine considering source data absence," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    4. Wang, Shaoxuan & Ge, Daochuan & Yong, Nuo & Sun, Ming & Yao, Yuantao & Tao, Longlong & Xia, Dongqin & Wang, Feipeng & Yu, Jie, 2025. "Rapid computation of survival signature for dynamic fault tree based on sequential binary decision diagram and multidimensional array," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    5. Li, Hao & Jiao, Jinyang & Liu, Zongyang & Lin, Jing & Zhang, Tian & Liu, Hanyang, 2025. "Trustworthy Bayesian deep learning framework for uncertainty quantification and confidence calibration: Application in machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    6. Gong, Ying & Wang, Yongzheng & Xie, Yuanhang & Peng, Xuzhang & Peng, Yan & Zhang, Wenhua, 2025. "Dynamic fusion LSTM-Transformer for prediction in energy harvesting from human motions," Energy, Elsevier, vol. 327(C).
    7. Yu, Haibo & Chang, Ling & Yang, Minghan & Chen, Shuai & Li, Huijuan & Wang, Jianye, 2025. "Time series modeling and forecasting with feature decomposition and interaction for prognostics and health management in nuclear power plant," Energy, Elsevier, vol. 324(C).
    8. Sicong Wan & Jichong Lei, 2025. "Research on a Small Modular Reactor Fault Diagnosis System Based on the Attention Mechanism," Energies, MDPI, vol. 18(14), pages 1-20, July.
    9. Zhou, Shiqi & Lin, Meng & He, Jun & Wu, Yuzeng & Wang, Xu, 2025. "Unsupervised clustering research of nuclear power plants under unlabeled unknown fault diagnosis scenario," Energy, Elsevier, vol. 326(C).
    10. Ma, Qiuju & Chen, Zhennan & Chen, Jianhua & Du, Mengzhen & Sun, Yubo & Chen, Nan, 2025. "A predictive model for centerline temperature in electrical cabinet fires," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).

  2. Yao, Jiachi & Chang, Zhonghao & Han, Te & Tian, Jingpeng, 2024. "Semi-supervised adversarial deep learning for capacity estimation of battery energy storage systems," Energy, Elsevier, vol. 294(C).

    Cited by:

    1. Zhao, Xiaoyu & Wang, Zuolu & Miao, Haiyan & Yang, Wenxian & Gu, Fengshou & Ball, Andrew D., 2024. "A label-free battery state of health estimation method based on adversarial multi-domain adaptation network and relaxation voltage," Energy, Elsevier, vol. 308(C).
    2. Wu, Rui & Tian, Jinpeng & Yao, Jiachi & Han, Te & Hu, Chunsheng, 2025. "Confidence-aware quantile Transformer for reliable degradation prediction of battery energy storage systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).

  3. Cheng, Yongbo & Qv, Junheng & Feng, Ke & Han, Te, 2024. "A Bayesian adversarial probsparse Transformer model for long-term remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 248(C).

    Cited by:

    1. Xiao, Xiao & Song, Meiqi & Liu, Xiaojing, 2025. "A reliable and adaptive prediction framework for nuclear power plant system through an improved Transformer model and Bayesian uncertainty analysis," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    2. Wang, Haoyu & Li, Chuanjiang & Ding, Peng & Li, Shaobo & Li, Tandong & Liu, Chenyu & Zhang, Xiangjie & Hong, Zejian, 2024. "A novel transformer-based few-shot learning method for intelligent fault diagnosis with noisy labels under varying working conditions," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    3. Wang, Xin & Jiang, Hongkai & Mu, Mingzhe & Dong, Yutong, 2025. "A dynamic collaborative adversarial domain adaptation network for unsupervised rotating machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    4. Wang, Lin & Guo, Wannian & Guo, Junyu & Zheng, Shaocong & Wang, Zhiyuan & Kang, Hooi Siang & Li, He, 2025. "An integrated deep learning model for intelligent recognition of long-distance natural gas pipeline features," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    5. Wu, Rui & Tian, Jinpeng & Yao, Jiachi & Han, Te & Hu, Chunsheng, 2025. "Confidence-aware quantile Transformer for reliable degradation prediction of battery energy storage systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).

  4. 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).

    Cited by:

    1. Dong, Manman & Cheng, Yongbo & Wan, Liangqi, 2024. "A new adaptive multi-kernel relevance vector regression for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Sonthalia, Ankit & Femilda Josephin, J.S. & Varuvel, Edwin Geo & Chinnathambi, Arunachalam & Subramanian, Thiyagarajan & Kiani, Farzad, 2025. "A deep learning multi-feature based fusion model for predicting the state of health of lithium-ion batteries," Energy, Elsevier, vol. 317(C).
    3. Tao, Junjie & Wang, Shunli & Cao, Wen & Fernandez, Carlos & Blaabjerg, Frede & Cheng, Liangwei, 2025. "An innovative multitask learning - Long short-term memory neural network for the online anti-aging state of charge estimation of lithium-ion batteries adaptive to varying temperature and current condi," Energy, Elsevier, vol. 314(C).
    4. Liu, Donglei & Wang, Shunli & Fan, Yongcun & Fernandez, Carlos & Blaabjerg, Frede, 2024. "An optimized multi-segment long short-term memory network strategy for power lithium-ion battery state of charge estimation adaptive wide temperatures," Energy, Elsevier, vol. 304(C).
    5. Bao, Xinyuan & Chen, Liping & Lopes, António M. & Li, Xin & Xie, Siqiang & Li, Penghua & Chen, YangQuan, 2023. "Hybrid deep neural network with dimension attention for state-of-health estimation of Lithium-ion Batteries," Energy, Elsevier, vol. 278(C).
    6. Liang, Pengfei & Tian, Jiaye & Wang, Suiyan & Yuan, Xiaoming, 2024. "Multi-source information joint transfer diagnosis for rolling bearing with unknown faults via wavelet transform and an improved domain adaptation network," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    7. Nak-Hun Choi & Jung Woo Sohn & Jong-Seok Oh, 2023. "Defect Detection Model Using CNN and Image Augmentation for Seat Foaming Process," Mathematics, MDPI, vol. 11(24), pages 1-13, December.
    8. Li, Lei & Li, Yuanjiang & Mao, Runze & Li, Yueling & Lu, Weizhi & Zhang, Jinglin, 2024. "TPANet: A novel triple parallel attention network approach for remaining useful life prediction of lithium-ion batteries," Energy, Elsevier, vol. 309(C).
    9. Wang, Huan & Li, Yan-Fu & Zhang, Ying, 2023. "Bioinspired spiking spatiotemporal attention framework for lithium-ion batteries state-of-health estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    10. Xu, Yiming & Ge, Xiaohua & Guo, Ruohan & Shen, Weixiang, 2025. "Recent advances in model-based fault diagnosis for lithium-ion batteries: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    11. Chen, Si-Zhe & Liu, Jing & Yuan, Haoliang & Tao, Yibin & Xu, Fangyuan & Yang, Ling, 2025. "AM-MFF: A multi-feature fusion framework based on attention mechanism for robust and interpretable lithium-ion battery state of health estimation," Applied Energy, Elsevier, vol. 381(C).
    12. Wu, Ji & Wang, Jieming & Lin, Mingqiang & Meng, Jinhao, 2025. "Retired battery capacity screening based on deep learning with embedded feature smoothing under massive imbalanced data," Energy, Elsevier, vol. 318(C).
    13. Soo, Yin-Yi & Wang, Yujie & Xiang, Haoxiang & Chen, Zonghai, 2024. "Machine learning based battery pack health prediction using real-world data," Energy, Elsevier, vol. 308(C).
    14. Deng, Congying & Deng, Zihao & Miao, Jianguo, 2024. "Semi-supervised ensemble fault diagnosis method based on adversarial decoupled auto-encoder with extremely limited labels," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    15. Zhang, Ran & Ji, ChunHui & Zhou, Xing & Liu, Tianyu & Jin, Guang & Pan, Zhengqiang & Liu, Yajie, 2024. "Capacity estimation of lithium-ion batteries with uncertainty quantification based on temporal convolutional network and Gaussian process regression," Energy, Elsevier, vol. 297(C).
    16. Xiong, Ran & Wang, Shunli & Huang, Qi & Yu, Chunmei & Fernandez, Carlos & Xiao, Wei & Jia, Jun & Guerrero, Josep M., 2024. "Improved cooperative competitive particle swarm optimization and nonlinear coefficient temperature decreasing simulated annealing-back propagation methods for state of health estimation of energy stor," Energy, Elsevier, vol. 292(C).
    17. Zhao, Bo & Zhang, Weige & Zhang, Yanru & Zhang, Caiping & Zhang, Chi & Zhang, Junwei, 2025. "Lithium-ion battery remaining useful life prediction based on interpretable deep learning and network parameter optimization," Applied Energy, Elsevier, vol. 379(C).
    18. Liu, Jiale & Wang, Huan, 2024. "A brain-inspired energy-efficient Wide Spiking Residual Attention Framework for intelligent fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    19. Guangyi Yang & Xianglin Wang & Ran Li & Xiaoyu Zhang, 2024. "State of Health Estimation for Lithium-Ion Batteries Based on Transferable Long Short-Term Memory Optimized Using Harris Hawk Algorithm," Sustainability, MDPI, vol. 16(15), pages 1-19, July.
    20. Yao, Jiachi & Chang, Zhonghao & Han, Te & Tian, Jingpeng, 2024. "Semi-supervised adversarial deep learning for capacity estimation of battery energy storage systems," Energy, Elsevier, vol. 294(C).
    21. Fahmy, Hend M. & Alqahtani, Ayedh H. & Hasanien, Hany M., 2024. "Precise modeling of lithium-ion battery in industrial applications using Walrus optimization algorithm," Energy, Elsevier, vol. 294(C).
    22. Wu, Rui & Tian, Jinpeng & Yao, Jiachi & Han, Te & Hu, Chunsheng, 2025. "Confidence-aware quantile Transformer for reliable degradation prediction of battery energy storage systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    23. Chen, Guanxu & Yang, Fangfang & Peng, Weiwen & Fan, Yuqian & Lyu, Ximin, 2024. "State-of-health estimation for lithium-ion batteries based on Kullback–Leibler divergence and a retentive network," Applied Energy, Elsevier, vol. 376(PB).

  5. 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).

    Cited by:

    1. Su, Yunsheng & Shi, Luojie & Zhou, Kai & Bai, Guangxing & Wang, Zequn, 2024. "Knowledge-informed deep networks for robust fault diagnosis of rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    2. Li, Jimeng & Mao, Weilin & Yang, Bixin & Meng, Zong & Tong, Kai & Yu, Shancheng, 2024. "RUL prediction of rolling bearings across working conditions based on multi-scale convolutional parallel memory domain adaptation network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Wang, Jingyuan & Liu, Zhen & Yao, Xutian & Wang, Yong & Li, Qi & Mi, Jinhua, 2025. "A sequential diagnostic strategy generation transformation method for large-scale systems based on multi-signal flow graph model and multi-objective optimization," Reliability Engineering and System Safety, Elsevier, vol. 259(C).
    4. Zhou, Tao & Yao, Dechen & Yang, Jianwei & Meng, Chang & Li, Ankang & Li, Xi, 2024. "DRSwin-ST: An intelligent fault diagnosis framework based on dynamic threshold noise reduction and sparse transformer with Shifted Windows," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    5. Gao, Dawei & Huang, Kai & Zhu, Yongsheng & Zhu, Linbo & Yan, Ke & Ren, Zhijun & Guedes Soares, C., 2024. "Semi-supervised small sample fault diagnosis under a wide range of speed variation conditions based on uncertainty analysis," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    6. Li, Hao & Jiao, Jinyang & Liu, Zongyang & Lin, Jing & Zhang, Tian & Liu, Hanyang, 2025. "Trustworthy Bayesian deep learning framework for uncertainty quantification and confidence calibration: Application in machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    7. 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).
    8. Huang, Keke & Tao, Shijun & Wu, Dehao & Yang, Chunhua & Gui, Weihua, 2024. "Robust condition identification against label noise in industrial processes based on trusted connection dictionary learning," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    9. Zhang, Xiao & Huang, Weiguo & Wang, Jun & Zhu, Zhongkui & Shen, Changqing & Chen, Kai & Zhong, Xingli & He, Li, 2025. "Adaptive variational sampling-embedded domain generalization network for fault diagnosis with intra-inter-domain class imbalance," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    10. 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).

  6. Meng, Huixing & Geng, Mengyao & Han, Te, 2023. "Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis," Reliability Engineering and System Safety, Elsevier, vol. 236(C).

    Cited by:

    1. Peng, Dandan & Desmet, Wim & Gryllias, Konstantinos, 2025. "Reconstruction-based Deep Unsupervised Adaptive Threshold Support Vector Data Description for wind turbine anomaly detection," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    2. Dong, Manman & Cheng, Yongbo & Wan, Liangqi, 2024. "A new adaptive multi-kernel relevance vector regression for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Chen, Zhen & Wang, Zirong & Wu, Wei & Xia, Tangbin & Pan, Ershun, 2024. "A hybrid battery degradation model combining arrhenius equation and neural network for capacity prediction under time-varying operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    4. Sercan Yalçın & Münür Sacit Herdem, 2024. "Optimizing EV Battery Management: Advanced Hybrid Reinforcement Learning Models for Efficient Charging and Discharging," Energies, MDPI, vol. 17(12), pages 1-21, June.
    5. Zhang, Ying & Gao, Kaiye & Ma, Tianyi & Wang, Huan & Li, Yan-Fu, 2024. "Intelligent recognition of structural health state of EV lithium-ion Battery using transfer learning based on X-ray computed tomography," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    6. Liang, Pengfei & Wang, Xiangfeng & Ai, Chao & Hou, Dongming & Liu, Siyuan, 2025. "SRSGCN: A novel multi-sensor fault diagnosis method for hydraulic axial piston pump with limited data," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    7. Wang, Zhanwei & Qin, Yijie & Kong, Yifan & Wang, Lin & Leng, Qiang & Zhang, Chunxiao, 2025. "Advanced fault detection, diagnosis and prognosis in HVAC systems: Lifecycle insight, key challenges, and promising approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 219(C).
    8. Wu, Jian & Meng, Jinhao & Lin, Mingqiang & Wang, Wei & Wu, Ji & Stroe, Daniel-Ioan, 2024. "Lithium-ion battery state of health estimation using a hybrid model with electrochemical impedance spectroscopy," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    9. Zhao, Hongqian & Chen, Zheng & Shu, Xing & Xiao, Renxin & Shen, Jiangwei & Liu, Yu & Liu, Yonggang, 2024. "Online surface temperature prediction and abnormal diagnosis of lithium-ion batteries based on hybrid neural network and fault threshold optimization," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    10. 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).
    11. Cao, Shihao & Wang, Zhihua & Wu, Qiong & Ouyang, Xiangmin & Si, Xiaosheng & Liu, Chengrui, 2025. "Failure time analysis for compound degradation procedures involving linear path and negative jumps," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    12. Liang, Pengfei & Tian, Jiaye & Wang, Suiyan & Yuan, Xiaoming, 2024. "Multi-source information joint transfer diagnosis for rolling bearing with unknown faults via wavelet transform and an improved domain adaptation network," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    13. Wang, Lubing & Zhao, Xufeng & Pham, Hoang, 2025. "Novel formulations and metaheuristic algorithms for predictive maintenance of aircraft engines with remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    14. Zhang, Zongjun & He, Wei & Zhou, Guohui & Li, Hongyu & Cao, You, 2025. "A new interpretable behavior prediction method based on belief rule base with rule reliability measurement," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    15. Wang, Haoyu & Li, Chuanjiang & Ding, Peng & Li, Shaobo & Li, Tandong & Liu, Chenyu & Zhang, Xiangjie & Hong, Zejian, 2024. "A novel transformer-based few-shot learning method for intelligent fault diagnosis with noisy labels under varying working conditions," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    16. Ye, Zhuang & Chang, Jiantao & Yu, Jianbo, 2025. "Prognosability regularized generative adversarial network for battery state of health estimation with limited samples," Energy, Elsevier, vol. 325(C).
    17. Wang, Huan & Li, Yan-Fu & Zhang, Ying, 2023. "Bioinspired spiking spatiotemporal attention framework for lithium-ion batteries state-of-health estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    18. Keshun, You & Puzhou, Wang & Peng, Huang & Yingkui, Gu, 2025. "A sound-vibration physical-information fusion constraint-guided deep learning method for rolling bearing fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    19. He, Zhongze & Wang, Shaoping & Shi, Jian & Liu, Di & Duan, Xiaochuan & Shang, Yaoxing, 2025. "Physics-informed neural network supported wiener process for degradation modeling and reliability prediction," Reliability Engineering and System Safety, Elsevier, vol. 258(C).
    20. Wang, Fengfei & Tang, Shengjin & Han, Xuebing & Yu, Chuanqiang & Sun, Xiaoyan & Lu, Languang & Ouyang, Minggao, 2024. "Capacity prediction of lithium-ion batteries with fusing aging information," Energy, Elsevier, vol. 293(C).
    21. Xing, Xueqi & Yan, Tongtong & Xia, Min, 2025. "Early prediction of battery life using an interpretable health indicator with evolutionary computing," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    22. Sun, Jing & Wang, Haitao, 2025. "State of health estimation for lithium-ion batteries based on optimal feature subset algorithm," Energy, Elsevier, vol. 322(C).
    23. Guo, Yongfang & Yu, Xiangyuan & Wang, Yashuang & Huang, Kai, 2024. "Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    24. Zhang, Jianping & Zhang, Yinjie & Fu, Jian & Zhao, Dawen & Liu, Ping & Zhang, Zhiwei, 2024. "Capacity fading knee-point recognition method and life prediction for lithium-ion batteries using segmented capacity degradation model," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    25. Li, Yanming & Qin, Xiaojuan & Chai, Min & Wu, Haoran & Zhang, Fujing & Jiang, Fenghe & Wen, Changbao, 2025. "SOH evaluation and RUL estimation of lithium-ion batteries based on MC-CNN-TimesNet model," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    26. Wang, Zhe & Yang, Lechang & Fang, Xiaolei & Zhang, Hanxiao & Xie, Min, 2025. "Image-based remaining useful life prediction through adaptation from simulation to experimental domain," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    27. A., Faizanbasha & Rizwan, U., 2025. "Deep learning-stochastic ensemble for RUL prediction and predictive maintenance with dynamic mission abort policies," Reliability Engineering and System Safety, Elsevier, vol. 259(C).
    28. Eleftheroglou, Nick & Galanopoulos, Georgios & Loutas, Theodoros, 2024. "Similarity learning hidden semi-Markov model for adaptive prognostics of composite structures," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    29. Kim, Jaewon & Sin, Seunghwa & Kim, Jonghoon, 2024. "Early remaining-useful-life prediction applying discrete wavelet transform combined with improved semi-empirical model for high-fidelity in battery energy storage system," Energy, Elsevier, vol. 297(C).
    30. Wu, Jiawei & Wan, Liangqi, 2024. "Reliability sensitivity analysis for RBSMC: A high-efficiency multiple response Gaussian process model," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    31. Liu, Ruonan & Xie, Yunfei & Lin, Di & Zhang, Weidong & Ding, Steven X., 2024. "Information-based Gradient enhanced Causal Learning Graph Neural Network for fault diagnosis of complex industrial processes," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    32. Chen, Bingyang & Zeng, Xingjie & Liu, Chao & Xu, Yafei & Cao, Heling, 2025. "Health management of power batteries in low temperatures based on Adaptive Transfer Enformer framework," Reliability Engineering and System Safety, Elsevier, vol. 254(PA).
    33. Ma, Yan & Li, Jiaqi & Gao, Jinwu & Chen, Hong, 2024. "State of health prediction of lithium-ion batteries under early partial data based on IWOA-BiLSTM with single feature," Energy, Elsevier, vol. 295(C).
    34. Tang, Aihua & Huang, Yukun & Xu, Yuchen & Hu, Yuanzhi & Yan, Fuwu & Tan, Yong & Jin, Xin & Yu, Quanqing, 2024. "Data-physics-driven estimation of battery state of charge and capacity," Energy, Elsevier, vol. 294(C).
    35. Liu, Jiale & Wang, Huan, 2024. "A brain-inspired energy-efficient Wide Spiking Residual Attention Framework for intelligent fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    36. 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).
    37. Wang, Fujin & Wu, Ziqian & Zhao, Zhibin & Zhai, Zhi & Wang, Chenxi & Chen, Xuefeng, 2024. "Physical knowledge guided state of health estimation of lithium-ion battery with limited segment data," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    38. Wei, Yujie & Pan, Ershun & Ye, Zhi-Sheng, 2024. "Condition monitoring based on corrupted multiple time series with common trends," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    39. Yao, Jiachi & Chang, Zhonghao & Han, Te & Tian, Jingpeng, 2024. "Semi-supervised adversarial deep learning for capacity estimation of battery energy storage systems," Energy, Elsevier, vol. 294(C).
    40. Yin, Xiuxian & He, Wei & Cao, You & Ma, Ning & Zhou, Guohui & Li, Hongyu, 2024. "A new health state assessment method based on interpretable belief rule base with bimetric balance," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    41. Wu, Rui & Tian, Jinpeng & Yao, Jiachi & Han, Te & Hu, Chunsheng, 2025. "Confidence-aware quantile Transformer for reliable degradation prediction of battery energy storage systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    42. Liu, Jie & He, Zihan & Miao, Yonghao, 2024. "Causality-based adversarial attacks for robust GNN modelling with application in fault detection," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    43. Che, Yunhong & Zheng, Yusheng & Forest, Florent Evariste & Sui, Xin & Hu, Xiaosong & Teodorescu, Remus, 2024. "Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    44. Jiang, Chen & Zhong, Teng & Choi, Hyunhee & Youn, Byeng D., 2025. "Physics-informed Gaussian process probabilistic modeling with multi-source data for prognostics of degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 258(C).
    45. Park, Hyung Jun & Kim, Nam H. & Choi, Joo-Ho, 2024. "A robust health prediction using Bayesian approach guided by physical constraints," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    46. 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).

  7. 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).

    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. 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).
    3. 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).
    4. 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).
    5. 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).
    6. 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).
    7. Zhang, Chao & Gong, Daqing & Xue, Gang, 2025. "An uncertainty-incorporated active data diffusion learning framework for few-shot equipment RUL prediction," Reliability Engineering and System Safety, Elsevier, vol. 254(PB).
    8. 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).
    9. Chen, Xu & Zhao, Chunhui & Ding, Jinliang, 2023. "Pyramid-type zero-shot learning model with multi-granularity hierarchical attributes for industrial fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    10. 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).
    11. 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).
    12. Ruicong Zhang & Yu Bao & Qinle Weng & Zhongtian Li & Yonggang Li, 2024. "Active domain adaptation method for label expansion problem," Journal of Risk and Reliability, , vol. 238(1), pages 3-15, February.
    13. 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).
    14. Li, Hao & Jiao, Jinyang & Liu, Zongyang & Lin, Jing & Zhang, Tian & Liu, Hanyang, 2025. "Trustworthy Bayesian deep learning framework for uncertainty quantification and confidence calibration: Application in machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    15. 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).
    16. 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).
    17. Wu, Hao & Xu, Yanwen & Liu, Zheng & Li, Yumeng & Wang, Pingfeng, 2023. "Adaptive machine learning with physics-based simulations for mean time to failure prediction of engineering systems," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    18. 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).
    19. 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).
    20. 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).
    21. 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).
    22. 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).
    23. Liu, Yanjun & Li, Hao & Yang, Yang & Zhu, Wenchao & Xie, Changjun & Yu, Xiaoran & Guo, Bingxin, 2025. "Reliability assessment of PEMFC aging prediction based on probabilistic Bayesian mixed recurrent neural networks," Renewable Energy, Elsevier, vol. 246(C).
    24. 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).
    25. 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).
    26. 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).
    27. 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).
    28. 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).
    29. Rathnakumar, Rahul & Pang, Yutian & Liu, Yongming, 2023. "Epistemic and aleatoric uncertainty quantification for crack detection using a Bayesian Boundary Aware Convolutional Network," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    30. 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).
    31. 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).
    32. 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).
    33. 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).
    34. 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).

  8. 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).

    Cited by:

    1. Dong, Manman & Cheng, Yongbo & Wan, Liangqi, 2024. "A new adaptive multi-kernel relevance vector regression for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Han, Peng & Huang, Zhiqiu & Li, Weiwei & He, Wei & Cao, You, 2025. "Trustworthy interval prediction method with uncertainty estimation based on evidence neural networks," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    3. Wang, Weicheng & Li, Chao & Zhang, Zhipeng & Chen, Jinglong & He, Shuilong & Feng, Yong, 2025. "Pseudo-label assisted contrastive learning model for unsupervised open-set domain adaptation in fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 254(PB).
    4. Lin, Yanzhuo & Wang, Yu & Zhang, Mingquan & Zhao, Ming, 2025. "A robust source-free unsupervised domain adaptation method based on uncertainty measure and adaptive calibration for rotating machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    5. Reza Bazghandi & Mohammad Hoseintabar Marzebali & Vahid Abolghasemi & Shahin Hedayati Kia, 2023. "A Novel Mode Un-Mixing Approach in Variational Mode Decomposition for Fault Detection in Wound Rotor Induction Machines," Energies, MDPI, vol. 16(14), pages 1-17, July.
    6. Du, Zhengyu & Liu, Dongdong & Cui, Lingli, 2025. "Dynamic model-driven dictionary learning-inspired domain adaptation strategy for cross-domain bearing fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 258(C).
    7. 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).
    8. Li, Yan-Fu & Wang, Huan & Sun, Muxia, 2024. "ChatGPT-like large-scale foundation models for prognostics and health management: A survey and roadmaps," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    9. Tian, Jilun & Zhang, Jiusi & Jiang, Yuchen & Wu, Shimeng & Luo, Hao & Yin, Shen, 2024. "A novel generalized source-free domain adaptation approach for cross-domain industrial fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    10. Ma, Liang & Li, Yannan & Zhang, Tieling & Tian, Jinpeng & Guo, Qinghua & Guo, Shanshan & Hu, Chunsheng & Chung, Chi Yung, 2025. "Trustworthy battery state of charge estimation enabled by multi-task deep learning," Energy, Elsevier, vol. 326(C).
    11. 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).
    12. Ma, Yulin & Yang, Jun & Li, Lei, 2023. "Gradient aligned domain generalization with a mutual teaching teacher-student network for intelligent fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    13. Cao, Yudong & Jia, Minping & Zhao, Xiaoli & Yan, Xiaoan & Feng, Ke, 2024. "Complex augmented representation network for transferable health prognosis of rolling bearing considering dynamic covariate shift," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    14. Chen, Fei & Ding, Chen & Hu, Xiaoxi & He, Xianghui & Yin, Xiuxing & Yang, Jiandong & Zhao, Zhigao, 2025. "Tensor Poincaré plot index: A novel nonlinear dynamic method for extracting abnormal state information of pumped storage units," Reliability Engineering and System Safety, Elsevier, vol. 254(PB).
    15. Wan, Liangqi & Wei, Yumeng & Zhang, Qiaoke & Liu, Lei & Chen, Yuejian, 2025. "A new multiple stochastic Kriging model for active learning surrogate-assisted reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    16. Liu, Yuanhong & Shi, Baoxin & Lu, Shixiang & Gao, Zhi-Wei & Zhang, Fangfang, 2024. "A novel local linear embedding algorithm via local mutual representation for bearing fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    17. Dong, Yutong & Jiang, Hongkai & Wang, Xin & Mu, Mingzhe & Jiang, Wenxin, 2024. "An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    18. Zhou, Tao & Yao, Dechen & Yang, Jianwei & Meng, Chang & Li, Ankang & Li, Xi, 2024. "DRSwin-ST: An intelligent fault diagnosis framework based on dynamic threshold noise reduction and sparse transformer with Shifted Windows," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    19. Li, Hao & Jiao, Jinyang & Liu, Zongyang & Lin, Jing & Zhang, Tian & Liu, Hanyang, 2025. "Trustworthy Bayesian deep learning framework for uncertainty quantification and confidence calibration: Application in machinery fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    20. Wang, Huan & Li, Yan-Fu, 2023. "Bioinspired membrane learnable spiking neural network for autonomous vehicle sensors fault diagnosis under open environments," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    21. 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).
    22. 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).
    23. Chen, Yinuo & Tian, Zhigang & Wei, Haotian & Dong, Shaohua, 2025. "Reconstruction of 3-D pipeline defect profile based on MFL signals and hybrid neural networks," Reliability Engineering and System Safety, Elsevier, vol. 258(C).
    24. 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).
    25. 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).
    26. Huang, Keke & Tao, Shijun & Wu, Dehao & Yang, Chunhua & Gui, Weihua, 2024. "Robust condition identification against label noise in industrial processes based on trusted connection dictionary learning," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    27. 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).
    28. Shao, Kaixuan & He, Yigang & Xing, Zhikai & Du, Bolun, 2023. "Detecting wind turbine anomalies using nonlinear dynamic parameters-assisted machine learning with normal samples," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    29. Hanting Zhou & Wenhe Chen & Jing Liu & Longsheng Cheng & Min Xia, 2024. "Trustworthy and intelligent fault diagnosis with effective denoising and evidential stacked GRU neural network," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3523-3542, October.
    30. Wenhao Lu & Wei Wang & Xuefei Qin & Zhiqiang Cai, 2024. "Enhancing Fault Diagnosis in Mechanical Systems with Graph Neural Networks Addressing Class Imbalance," Mathematics, MDPI, vol. 12(13), pages 1-22, July.
    31. 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).
    32. 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).
    33. 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).
    34. Wei, Yujie & Pan, Ershun & Ye, Zhi-Sheng, 2024. "Condition monitoring based on corrupted multiple time series with common trends," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    35. 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).
    36. 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).
    37. Zhang, Qing & Tang, Lv & Xuan, Jianping & Shi, Tielin & Li, Rui, 2023. "An uncertainty relevance metric-based domain adaptation fault diagnosis method to overcome class relevance caused confusion," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    38. Das, Laya & Gjorgiev, Blazhe & Sansavini, Giovanni, 2024. "Uncertainty-aware deep learning for monitoring and fault diagnosis from synthetic data," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    39. Sun, Jiechen & Zhou, Funa & Hu, Xiong & Wang, Chaoge & Wang, Tianzhen, 2025. "Personalized federated learning for remaining useful life prediction under scenarios of fragmented out-of-distribution data," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    40. 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).

  9. Li, Xin & Zhong, Xiang & Shao, Haidong & Han, Te & Shen, Changqing, 2021. "Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

    Cited by:

    1. Tan, Hongchuang & Xie, Suchao & Ma, Wen & Yang, Chengxing & Zheng, Shiwei, 2023. "Correlation feature distribution matching for fault diagnosis of machines," Reliability Engineering and System Safety, Elsevier, vol. 231(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. Li, Yan-Fu & Wang, Huan & Sun, Muxia, 2024. "ChatGPT-like large-scale foundation models for prognostics and health management: A survey and roadmaps," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    4. Shi, Yaowei & Deng, Aidong & Deng, Minqiang & Xu, Meng & Liu, Yang & Ding, Xue & Li, Jing, 2022. "Transferable adaptive channel attention module for unsupervised cross-domain fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Shi, Yaowei & Deng, Aidong & Deng, Minqiang & Xu, Meng & Liu, Yang & Ding, Xue & Bian, Wenbin, 2023. "Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Liu, Shaowei & Jiang, Hongkai & Wu, Zhenghong & Yi, Zichun & Wang, Ruixin, 2023. "Intelligent fault diagnosis of rotating machinery using a multi-source domain adaptation network with adversarial discrepancy matching," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    7. Gao, Dawei & Huang, Kai & Zhu, Yongsheng & Zhu, Linbo & Yan, Ke & Ren, Zhijun & Guedes Soares, C., 2024. "Semi-supervised small sample fault diagnosis under a wide range of speed variation conditions based on uncertainty analysis," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    8. Na, Kyumin & Yoon, Heonjun & Kim, Jaedong & Kim, Sungjong & Youn, Byeng D., 2023. "PERL: Probabilistic energy-ratio-based localization for boiler tube leaks using descriptors of acoustic emission signals," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    9. 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).
    10. Zhang, Zhongwei & Jiao, Zonghao & Li, Youjia & Shao, Mingyu & Dai, Xiangjun, 2024. "Intelligent fault diagnosis of bearings driven by double-level data fusion based on multichannel sample fusion and feature fusion under time-varying speed conditions," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    11. 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).
    12. 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).
    13. 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).
    14. Zhang, Xinwei & Feng, Yong & Chen, Jinglong & Liu, Zijun & Wang, Jun & Huang, Hong, 2024. "Knowledge distillation-optimized two-stage anomaly detection for liquid rocket engine with missing multimodal data," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    15. Zhang, Qing & Li, Shaochen & Chin-Hon, Tan & Liu, Xiaofei & Shen, Jingyuan & Shi, Tielin & Xuan, Jianping, 2025. "Fault Impulse Inference and Cyclostationary Approximation: A feature-interpretable intelligent fault detection method for few-shot unsupervised domain adaptation," Reliability Engineering and System Safety, Elsevier, vol. 253(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).

  10. Zhenyu He & Xiaochen Zhang & Chao Liu & Te Han, 2020. "Fault Prognostics for Photovoltaic Inverter Based on Fast Clustering Algorithm and Gaussian Mixture Model," Energies, MDPI, vol. 13(18), pages 1-20, September.

    Cited by:

    1. Tarek Berghout & Mohamed Benbouzid & Leïla-Hayet Mouss, 2021. "Leveraging Label Information in a Knowledge-Driven Approach for Rolling-Element Bearings Remaining Useful Life Prediction," Energies, MDPI, vol. 14(8), pages 1-18, April.
    2. Kuei-Hsiang Chao & Chen-Hou Ke, 2020. "Fault Diagnosis and Tolerant Control of Three-Level Neutral-Point Clamped Inverters in Motor Drives," Energies, MDPI, vol. 13(23), pages 1-25, November.
    3. Varaha Satra Bharath Kurukuru & Ahteshamul Haque & Mohammed Ali Khan & Subham Sahoo & Azra Malik & Frede Blaabjerg, 2021. "A Review on Artificial Intelligence Applications for Grid-Connected Solar Photovoltaic Systems," Energies, MDPI, vol. 14(15), pages 1-35, August.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.