4.6 Article

System-level prognostics approach for failure prediction of reaction wheel motor in satellites

期刊

ADVANCES IN SPACE RESEARCH
卷 71, 期 6, 页码 2691-2701

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ELSEVIER SCI LTD
DOI: 10.1016/j.asr.2022.11.028

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Accelerated life test; Extended Kalman filter; Particle filter; Prognostics; Reaction wheel motor; Satellite

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This study proposes a system-level prognostics approach for the reaction wheel motor, which is widely used for advanced attitude control of satellites. By considering the motor as a system composed of multiple components, the approach estimates the health degradation and predicts failures based on motor operation data obtained during accelerated-life tests.
The reaction wheels actuated by motors are widely used for advanced attitude control of satellites. During the satellite operation, the performance of reaction wheel motor degrades and results in unexpected failures. To guarantee the reliability and safety of satellites, it is important to predict its remaining useful life while it is in operation. To address this issue, this study presents a system-level prognostics approach for the reaction wheel motor, by regarding it as a system composed of multiple components. The approach is demonstrated by using the motor operation data obtained during the accelerated-life tests on ground for 3 years. Health degradation of each components of the motor are estimated using the adaptive extended Kalman filter. Failure threshold of the motor performance is established by the design requirement on characteristic curve. The anomaly detection and failure prediction are performed using the shifting kernel particle filter. (c) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

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