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

Abstract

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.