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

作者：Gueddi Imen; Nasri Othman^*; Benothman Kamal; Dague Philippe

来源：International Journal of Control Automation and Systems, 2017, 15(2): 776-789.

DOI：10.1007/s12555-015-0258-x

• Fault detection and isolation
• MSR
• PCA
• reconstruction
• SPE
• thrusters
• VPCA

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.

• 出版日期2017-4
• 单位INRIA