Abstract
The propulsion system in a spacecraft is an important subsystem for orbit transfer and attitude control. A fast and accurate fault diagnosis system contributes to the safety of the entire system. As the system becomes more complex, identifying faults, their locations, and root causes becomes increasingly difficult. This study utilized Principal Component Analysis (PCA) and feature optimization with Fast Fourier Transform (FFT) analysis using greedy algorithm to achieve fault diagnosis systems for spacecraft to replace the current operation based on the expert knowledge. By applying PCA to simulation data for the faults were successfully detected and their locations and root causes identified.
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