Remaining useful life prediction for complex systems considering varying future operational conditions

Author:

Chang Liang1ORCID,Lin Yan‐Hui1ORCID,Zio Enrico23

Affiliation:

1. School of Reliability and Systems Engineering Beihang University Beijing China

2. Energy Department Politecnico di Milano Milan Italy

3. Mines ParisTech PSL University, Centre for research on Risk and Crises (CRC) Sophia‐Antipolis France

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Management Science and Operations Research,Safety, Risk, Reliability and Quality

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep alloys: Metal materials empowered by deep learning;Materials Science in Semiconductor Processing;2024-08

2. Remaining Useful Life Estimation of Aircraft Engines Using Siamese Attention-Augmented Quantum Convolutional Neural Networks;2024 5th International Conference on Computer Engineering and Application (ICCEA);2024-04-12

3. Platform health management for aircraft maintenance – a review;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2024-01-13

4. DESIGN OF A RISK MODEL AND ANALYTICAL DECISION INFORMATION SYSTEM FOR POWER OPERATION IN THE CONTEXT OF SMART GRID;INT J POWER ENERGY S;2024

5. A novel deep time‐index framework with limited data and feature extraction for battery capacity degradation prediction;Quality and Reliability Engineering International;2023-10-13

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