Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions

Citations

Cited by:

1. Nannan Xu & Xinze Cui & Xin Wang & Wei Zhang & Tianyu Zhao, 2022. "An Intelligent Athlete Signal Processing Methodology for Balance Control Ability Assessment with Multi-Headed Self-Attention Mechanism," Mathematics, MDPI, vol. 10(15), pages 1-16, August.
2. Li, Xuanlin & Hu, Yawei & Wang, Hang & Liu, Yongbin & Liu, Xianzeng & Lu, Huitian, 2025. "A closed-form continuous-depth neural-based hybrid difference features re-representation network for RUL prediction," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
3. Zhang, Jiusi & Tian, Jilun & Yan, Pengfei & Wu, Shimeng & Luo, Hao & Yin, Shen, 2024. "Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
4. Murray, Brian & Perera, Lokukaluge Prasad, 2021. "An AIS-based deep learning framework for regional ship behavior prediction," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
5. Chen, Chong & Liu, Ying & Sun, Xianfang & Cairano-Gilfedder, Carla Di & Titmus, Scott, 2021. "An integrated deep learning-based approach for automobile maintenance prediction with GIS data," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
6. Yi Lyu & Qichen Zhang & Zhenfei Wen & Aiguo Chen, 2022. "Remaining Useful Life Prediction Based on Multi-Representation Domain Adaptation," Mathematics, MDPI, vol. 10(24), pages 1-18, December.
7. 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).
8. Jiaxian Chen & Dongpeng Li & Ruyi Huang & Zhuyun Chen & Weihua Li, 2025. "A transfer regression network-based adaptive calibration method for remaining useful life prediction considering individual discrepancies in the degradation process of machinery," Journal of Intelligent Manufacturing, Springer, vol. 36(4), pages 2767-2783, April.
9. Xiang, Sheng & Li, Penghua & Huang, Yi & Luo, Jun & Qin, Yi, 2024. "Single gated RNN with differential weighted information storage mechanism and its application to machine RUL prediction," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
10. Wei, Yupeng & Wu, Dazhong & Terpenny, Janis, 2021. "Learning the health index of complex systems using dynamic conditional variational autoencoders," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
11. Lefa Zhao & Yafei Zhu & Tianyu Zhao, 2022. "Deep Learning-Based Remaining Useful Life Prediction Method with Transformer Module and Random Forest," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
12. Xin Wang & Seyed Mehdi Abtahi & Mahmood Chahari & Tianyu Zhao, 2022. "An Adaptive Neuro-Fuzzy Model for Attitude Estimation and Control of a 3 DOF System," Mathematics, MDPI, vol. 10(6), pages 1-16, March.
13. Dong, Shaojiang & Xiao, Jiafeng & Hu, Xiaolin & Fang, Nengwei & Liu, Lanhui & Yao, Jinbao, 2023. "Deep transfer learning based on Bi-LSTM and attention for remaining useful life prediction of rolling bearing," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
14. Zhang, Xin & Sun, Jiankai & Wang, Jiaxu & Jin, Yulin & Wang, Lei & Liu, Zhiwen, 2023. "PAOLTransformer: Pruning-adaptive optimal lightweight Transformer model for aero-engine remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
15. Cheng, Han & Kong, Xianguang & Wang, Qibin & Ma, Hongbo & Yang, Shengkang, 2022. "The two-stage RUL prediction across operation conditions using deep transfer learning and insufficient degradation data," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
16. Yi Lyu & Zhenfei Wen & Aiguo Chen, 2025. "A novel transfer learning approach based on deep degradation feature adaptive alignment for remaining useful life prediction with multi-condition data," Journal of Intelligent Manufacturing, Springer, vol. 36(1), pages 619-637, January.
17. 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).
18. 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).
19. Guan, Yang & Meng, Zong & Sun, Dengyun & Liu, Jingbo & Fan, Fengjie, 2021. "2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
20. Lyu, Dongzhen & Niu, Guangxing & Liu, Enhui & Zhang, Bin & Chen, Gang & Yang, Tao & Zio, Enrico, 2022. "Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
21. Jiapei Peng & Lefa Zhao & Tianyu Zhao, 2022. "Study on Dynamic Characteristics of a Rotating Sandwich Porous Pre-Twist Blade with a Setting Angle Reinforced by Graphene Nanoplatelets," Mathematics, MDPI, vol. 10(15), pages 1-15, August.
22. Joma Aldrini & Ines Chihi & Lilia Sidhom, 2024. "Fault diagnosis and self-healing for smart manufacturing: a review," Journal of Intelligent Manufacturing, Springer, vol. 35(6), pages 2441-2473, August.
23. Zhang, Jiusi & Li, Xiang & Tian, Jilun & Jiang, Yuchen & Luo, Hao & Yin, Shen, 2023. "A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
24. Xia, Jun & Feng, Yunwen & Teng, Da & Chen, Junyu & Song, Zhicen, 2022. "Distance self-attention network method for remaining useful life estimation of aeroengine with parallel computing," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
25. Cheng, Han & Kong, Xianguang & Wang, Qibin & Ma, Hongbo & Yang, Shengkang & Xu, Kun, 2023. "Remaining useful life prediction combined dynamic model with transfer learning under insufficient degradation data," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
26. Xiong, Jiawei & Zhou, Jian & Ma, Yizhong & Zhang, Fengxia & Lin, Chenglong, 2023. "Adaptive deep learning-based remaining useful life prediction framework for systems with multiple failure patterns," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
27. González-Muñiz, Ana & Díaz, Ignacio & Cuadrado, Abel A. & García-Pérez, Diego, 2022. "Health indicator for machine condition monitoring built in the latent space of a deep autoencoder," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
28. Li, Tianfu & Zhao, Zhibin & Sun, Chuang & Yan, Ruqiang & Chen, Xuefeng, 2021. "Hierarchical attention graph convolutional network to fuse multi-sensor signals for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 215(C).