@inproceedings{b9671bef03c0443d9c8c421553518a55,
title = "Exchange problem optimization between aeroengines with multiple modules and life-limited parts",
abstract = "The exchange problem of modules and life-limited parts when two aeroengines are sent for the shop visit at the same time is studied. Taking the lowest total loss cost of modules maintenance and life-limited parts replacement as the optimization objective, this paper establishes a single-aeroengine opportunistic maintenance model. A heuristic search algorithm based on two reduction rules is used to improve search efficiency. The genetic algorithm is used to solve the problem that the solution space of the exchange problem is too large. Finally, numerical experiments and application cases are used to prove the efficiency of the algorithm. The results show that the exchange algorithm proposed in this paper can calculate the exchange scheme to reduce the loss cost of two aeroengines in a short time and the optimization rate is about 18\%.",
keywords = "Res-BP Neural Network, aero-engine, gas path parameter deviations, mean impact value",
author = "Bin Yu and Xuyun Fu and Wei Jiang and Zhengfeng Bai",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Prognostics and Health Management Conference, PHM-London 2022 ; Conference date: 27-05-2022 Through 29-05-2022",
year = "2022",
doi = "10.1109/PHM2022-London52454.2022.00024",
language = "英语",
series = "Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "90--96",
editor = "Chuan Li and Gianluca Valentino and Ling Kang and Diego Cabrera and Dejan Gjorgjevikj",
booktitle = "Proceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022",
address = "美国",
}