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Fault Detection and Isolation of Spacecraft Thrusters using an Extended Principal Component Analysis to Interval Data

Imen Gueddi, Othman Nasri*, Kamal Benothman, and Philippe Dague
International Journal of Control, Automation, and Systems, vol. 15, no. 2, pp.776-789, 2017

Abstract : "This paper presents a new interval diagnosis method to detect and isolate actuators faults of an autonomous spacecraft involved in the rendez-vous phase of the Mars Sample Return (MSR) mission. The proposed diagnosis approach is based on the Vertices Principal Component Analysis (VPCA) as an extension of the classical PCA method to interval data. To ensure the feasibility of the proposed Fault Detection and Isolation (FDI) approach, a set of interval data provided by the MSR “high-fidelity” industrial simulator and representing the opening rates of the spacecraft thrusters has been considered. The results have proven the efficiency of the proposed FDI approach in the diagnosing process assuring the detection and the isolation of both single and multiple faults."

Keyword : Fault detection and isolation, MSR, PCA, reconstruction, SPE, thrusters, VPCA.

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