Statistical Fault Detection and Isolation for Linear Time-Varying Systems

Abstract : This paper describes a statistical approach to fault detection and isolation for linear time-varying (LTV) systems subject to parametric additive faults. The proposed approach combines a GLR test with a recursive filter that cancels out the dynamics of the monitored faults effects. To our knowledge, the proposed recursive filter is new for the considered faults with time-varying profiles. The resulting algorithm handles fault diagnosis with weaker assumptions than usual, in particular on the number of sensors and on the stability of the monitored system.
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Communication dans un congrès
SYSID - 16th IFAC Symposium on System Identification, Jul 2012, Brussels, Belgium. 16 | Part 1, pp.625-630, 2012, 〈10.3182/20120711-3-BE-2027.00145〉
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https://hal.inria.fr/hal-00776898
Contributeur : Qinghua Zhang <>
Soumis le : mercredi 16 janvier 2013 - 14:31:53
Dernière modification le : vendredi 16 novembre 2018 - 01:31:11

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Qinghua Zhang, Michèle Basseville. Statistical Fault Detection and Isolation for Linear Time-Varying Systems. SYSID - 16th IFAC Symposium on System Identification, Jul 2012, Brussels, Belgium. 16 | Part 1, pp.625-630, 2012, 〈10.3182/20120711-3-BE-2027.00145〉. 〈hal-00776898〉

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