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Robust fault detection using consistency techniques for uncertainty handling
Gelso, Esteban Reinaldo; Castillo, Sandra M.; Armengol Llobet, Joaquim
Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system
25-05-2010
Anàlisi d'intervals (Matemàtica)
Errors de sistemes (Enginyeria)
Sistemes dinàmics diferenciables
Differentiable dynamical systems
Interval analysis (Mathematics)
System failures (Engineering)
Tots els drets reservats
Artículo
IEEE
         

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