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

다국어 초록 (Multilingual Abstract)

This paper presents a new interval diagnosis method to detect and isolate actuators faults of an autonomousspacecraft involved in the rendez-vous phase of the Mars Sample Return (MSR) mission. The proposeddiagnosis approach is based on the Vertices Principal Component Analysis (VPCA) as an extension of the classicalPCA 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 ofthe spacecraft thrusters has been considered. The results have proven the efficiency of the proposed FDI approachin the diagnosing process assuring the detection and the isolation of both single and multiple faults.

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