RUL Prediction of Reaction Wheel Motor in Satellites
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Abstract
For advanced agile attitude control of the satellite, reaction wheels are used actuated by motor. In order to ensure reliable operation, fault detection and prediction of remaining useful life (RUL) of the motor is of great importance. In this study, multi-scale Extended Kalman Filter (EKF) is employed for this purpose using the data of input current and output velocity measured in the life test of the motor. The motor dynamic behavior is modeled by the ordinary differential equations (ODEs). Characteristic behavior of the reaction wheel that degrades as the motor is used over repeated cycles is taken as the health indicator. The degradation value is defined by damping coefficient by solving the micro EKF problem using the input and output measurements at each cycle. Then, the RUL is predicted by solving the macro EKF problem based on the regression model of damping coefficient, which enables proactive action before the motor failure is encountered.
How to Cite
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motor, satellite, EKF, Remaining useful life, PHM
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