Fault diagnosability utilizing quasi-static and structural modelling |
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Institution: | 1. Technical University of Catalonia (UPC), 10 Rambla Sant Nebridi, 08222 Terrassa, Spain;2. LAAS-CNRS, University of Toulouse, 7, avenue du Colonel Roche, 31077 Toulouse Cedex 4, France |
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Abstract: | This paper presents a diagnosis model-based method to analyse fault discriminability and assess diagnosability. The technique is based on the state space representation of quasi-static models. Fault diagnosability characterises the faults that can be discriminated using the available sensors in a system. The method can be used to select the minimum set of sensors that guarantee discriminability of an anticipated set of faults. The approach is applied on a two-tanks system benchmark and is compared to a diagnosability analysis method based on structural analysis. |
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