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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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Contributor : Qinghua Zhang Connect in order to contact the contributor
Submitted on : Wednesday, January 16, 2013 - 2:31:53 PM
Last modification on : Friday, January 21, 2022 - 3:13:44 AM

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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. pp.625-630, ⟨10.3182/20120711-3-BE-2027.00145⟩. ⟨hal-00776898⟩



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