Research on Predictive Maintenance Architecture of Experimental Aircraft Based on Digital Twins

DOI

10.2991/978-94-6463-308-5_10How to use a DOI?

Keywords

digital twin; predictive maintenance; artificial intelligence algorithms; fault diagnosis; fault prediction

Abstract

With the rapid development of industrial technology and the new generation of information technology, the integration and intelligence of aircraft equipment continue to improve, increasing the probability of experimental aircraft malfunction and functional failures, resulting in a significant increase in flight test maintenance costs. To reduce downtime and maintenance costs, this article proposes a new predictive maintenance model for experimental aircraft based on digital twin technology, established a predictive maintenance process architecture for digital twin driven experimental aircraft, and elaborated on the operational mechanism of this architecture in detail. Taking twin data as the core, the information collection scheme and multidimensional virtual model scheme are constructed, and the fault diagnosis, fault trend prediction and maintenance scheme decision based on artificial intelligence are studied. A predictive maintenance process for experimental aircraft based on digital twins is presented, and key artificial intelligence algorithms are analyzed. This technology will help experimental aircraft improve flight efficiency, reduce equipment maintenance costs, and ensure the safety and reliability of the aircraft.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ziyue Liang
PY  - 2023
DA  - 2023/12/11
TI  - Research on Predictive Maintenance Architecture of Experimental Aircraft Based on Digital Twins
BT  - Proceedings of the 2023 8th International Conference on Engineering Management (ICEM 2023)
PB  - Atlantis Press
SP  - 88
EP  - 96
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-308-5_10
DO  - 10.2991/978-94-6463-308-5_10
ID  - Liang2023
ER  -