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Authors: Xunjia Li 1 ; Xin Ma 1 ; Tao Zhang 1 ; Xiaodong Han 2 and Yajie Liu 1

Affiliations: 1 College of System Engineering, National University of Defense Technology, Changsha 410073, China, China ; 2 Institute of Telecommunication Satellite, China Academy of Space Technology, Beijing 100081, China, China

Keyword(s): Autonomy, Fault detection, Recovery, Task re-planning, Artificial intelligence

Abstract: During the operation of the satellite in orbit, the operating state may change due to the fault. The impact of satellite failures on satellites is enormous. In this paper, satellite fault detection and recovery is taken as the research object, and an automatic fault detection and recovery framework (AFRF) for fault recognition and recovery of satellite autonomous operation and task re-planning is proposed. Artificial intelligence methods are used in the framework to implement on-board rapid diagnosis faults, autonomous fault repair, and autonomic task re-planning. The experimental results show that the proposed framework can solve the satellite fault problem well and has a good engineering application prospect.

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Paper citation in several formats:
Li, X.; Ma, X.; Zhang, T.; Han, X. and Liu, Y. (2020). Research on Satellite Autonomous Fault Detection and Recovery Framework. In Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - ICVMEE; ISBN 978-989-758-412-1; ISSN 2184-741X, SciTePress, pages 293-298. DOI: 10.5220/0008385602930298

@conference{icvmee20,
author={Xunjia Li. and Xin Ma. and Tao Zhang. and Xiaodong Han. and Yajie Liu.},
title={Research on Satellite Autonomous Fault Detection and Recovery Framework},
booktitle={Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - ICVMEE},
year={2020},
pages={293-298},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008385602930298},
isbn={978-989-758-412-1},
issn={2184-741X},
}

TY - CONF

JO - Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - ICVMEE
TI - Research on Satellite Autonomous Fault Detection and Recovery Framework
SN - 978-989-758-412-1
IS - 2184-741X
AU - Li, X.
AU - Ma, X.
AU - Zhang, T.
AU - Han, X.
AU - Liu, Y.
PY - 2020
SP - 293
EP - 298
DO - 10.5220/0008385602930298
PB - SciTePress

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