We propose a new framework for spacecraft fault diagnosis based on combined parameter and mode online estimation using a sequential Monte Carlo method. Our method can detect and diagnose faults as parameter changes and hence can be considered as a probabilistic approach for the parameter-estimation-based fault diagnosis method which is one of the methodologies on quantitative model-based diagnosis. We derive an algorithm for spacecraft fault diagnosis by describing the parameter-estimation-based fault diagnosis method as a probabilistic inference problem and applying a modified sequential Monte Carlo method, obtained by incorporating fault-modes, risk-sensitivities on modes and kernel-smoothing techniques into the original method, to the problem. The proposed fault-diagnosis algorithm was applied to an artificial data simulating malfunctions of thrusters in rendezvous maneuver of spacecraft, and the feasibility of the method was confirmed.
2007 The Japan Society for Aeronautical and Space Sciences