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Fault Detection and Isolation of spacecraft thrusters using an extended principal component analysis to interval data

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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.

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Author information

Authors and Affiliations

  1. LARATSI Lab, National Engineering School of Monastir (ENIM), Monastir Ibn El Jazzar, 5019, Tunisia

    Imen Gueddi

  2. National Engineering School of Sousse (ENISo), University of Sousse, Sousse, Tunisia

    Imen Gueddi

  3. LATIS Lab, National Engineering School of Sousse (ENISo), University of Sousse, BP 264, Sousse Erriadh, 4023, Tunisia

    Othman Nasri

  4. LARATSI Lab, National Engineering School of Monastir (ENIM), University of Monastir, Monastir Ibn El Jazzar, 5019, Tunisia

    Kamal Benothman

  5. LRI (Laboratory for Computer Science), University of Paris-Sud 11, CNRS & INRIA Saclay Île - de - France, Bt 650, 91405, Orsay Cedex, France

    Philippe Dague

Authors
  1. Imen Gueddi
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  2. Othman Nasri
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  3. Kamal Benothman
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  4. Philippe Dague
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Corresponding author

Correspondence to Othman Nasri.

Additional information

Recommended by Associate Editor Guang-Hong Yang under the direction of Editor Duk-Sun Shim. This work has been developed in the project SIRASAS (Strategies Innovantes et Robustes pour l’Autonomie des Systemes Aeronautiques et Spatiaux) supported by the Fondation de Recherche pour l’Aeronautique et l’Espace.

Imen Gueddi received her engineering degree in Industrial Electronics in 2012 and her Msc. degree in intelligent and communicating systems in 2013 from the National Engineering School of Sousse (ENISo), Tunisia. She is currently a Ph.D. student in the same university. Her interests research include fault diagnosis and interval arithmetic.

Othman Nasri was born in Kasserine, Tunisia. In July 2004 and December 2007 correspondingly, he received his Post-Graduate Degree in Control Systems and Applied Informatics from Ecole Centrale de Nantes-France and his Ph.D. degree in Signal Processing and Telecommunications from CentraleSupelec of Rennes-France. From 2008 to 2010, he was a research Engineer in Embedded Control Systems in CNRS-University of Paris-Sud 11 / INRIA Saclay Île-De-France. He is now an Associate Professor / Director of the Department of Industrial Electronics of National Engineering School of Sousse, university of Sousse - Tunisia. His research interests include fault diagnosis and FTC, process modeling and monitoring, multivariate statistical approaches, safety verification of hybrid systems.

Kamal Benothman received the license in Mechanical and Energetic Engineering in 1980 from the University of Valencienne, France. He obtained his engineering diploma in Mechanics and Energetic, an Msc. degree in Automatics and Signal Processing in 1981 and a Ph.D. in Automatics and Signal Processing in 1984 from the same University. He received his DSc degree from the National Engineering School of Tunis, Tunisia in 2008. He is currently a professor at the National Engineering School of Monastir (ENIM), University of Monastir, Tunisia. His interests include reliability, fault diagnosis, multi statistical process control, and fuzzy systems. He is a member of the Association of Electrician Specialists in Tunisia ASET.

Philippe Dague received his Msc. degrees in Mathematics from the University Paris 7 in 1971 and in Theoretical Physics from the University Paris 6 in 1972, engineering degree from “Ecole Centrale de Paris" in 1972 and Ph.D. degree in Theoretical Physics from the University Paris 6 in 1976. He was a Mathematics assistant professor at the University of Poitiers, then at the University Paris 6, from 1976 to 1983. From 1983 to 1992, he was a research engineer in Computer Science at the IBM Paris Scientific Center. He received the “Habilitation à Diriger des Recherches" degree in Computer Science in 1992 from the University Paris 6. From 1992 to 2005, he was full professor of Computer Science at the University Paris-Nord 13, where he founded in 1999 and led up to 2005 the “Artificial Learning, Diagnosis and Agents" group of the “Laboratoire d’Informatique de Paris-Nord" (LIPN). From 2005, he is full professor of Computer Science at the University Paris-Sud and was director from 2010 to 2014 of the “Laboratoire de Recherche en Informatique" (LRI, the Laboratory for Computer Science at University, joint with CNRS, the National Center for Scientific Research). His research activity from 1984 deals with Artificial Intelligence techniques (Knowledge Representation and Reasoning) for Engineering, in particular qualitative, causal and temporal modeling and reasoning, and model-based diagnosis (MBD) and supervision of complex systems. His active research topics from some years are: bridging the Control Engineering and the AI MBD approaches, building qualitative models from numeric design models, distributed diagnosis in a peer to peer framework, diagnosability and predictability analysis for distributed discrete-event systems. He applied these techniques to various fields: through partnerships with manufacturers, national and international projects: diagnosis of electronic, automotive and spatial systems, supervision of telecommunication networks, monitoring of Web services. He also works presently in bioinformatics on the analysis of metabolic networks. He has been member of the program committee of more than 60 conferences and of the evaluation committee of several national programs and is the author of more than 80 papers in international or national conferences and journals, and of several books chapters.

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Gueddi, I., Nasri, O., Benothman, K. et al. Fault Detection and Isolation of spacecraft thrusters using an extended principal component analysis to interval data. Int. J. Control Autom. Syst. 15, 776–789 (2017). https://doi.org/10.1007/s12555-015-0258-x

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