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Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction:Methodo-logies,Evaluation,and Future Trends

Yucheng Wang Mohamed Ragab Yubo Hou Min Wu Xiaoli Li Zhenghua Chen

自动化学报（英文版）2026，Vol.13Issue(8)：1783-1803,21.

自动化学报（英文版）2026，Vol.13Issue(8)：1783-1803,21.DOI:10.1109/JAS.2025.125843

Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction:Methodo-logies,Evaluation,and Future Trends

Yucheng Wang ¹Mohamed Ragab ²Yubo Hou ¹Min Wu ¹Xiaoli Li ³Zhenghua Chen⁴

作者信息

1. Institute for Infocomm Research,Agency for Science,Technology and Research,Singapore 649491,Singapore
2. Propulsion and Space Research Center,Technology Innovation Institute,Abu Dhabi 9639,The United Arab Emirates
3. Information Systems Technology and Design Pillar,Singapore University of Technology and Design,Singapore 487372,Singapore
4. James Watt School of Engineering,University of Glasgow,Glasgow G12 8QQ,UK
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摘要

关键词

Domain adaptation/fault prognosis/remaining use-ful life estimation/turbofan engines

Key words

Domain adaptation/fault prognosis/remaining use-ful life estimation/turbofan engines

引用本文复制引用

Yucheng Wang,Mohamed Ragab,Yubo Hou,Min Wu,Xiaoli Li,Zhenghua Chen..Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction:Methodo-logies,Evaluation,and Future Trends[J].自动化学报（英文版）,2026,13(8):1783-1803,21.

基金项目

This research was supported by the Agency for Science,Technology and Research(A*STAR)under its MTI WS Fund(W24MCMF012). （A*STAR）

自动化学报（英文版）

ISSN：2329-9266

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