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Abstract



Diagnosability Analysis Considering Causal Interpretations for Differential Constraints


This work is focused on structural approaches to studying diagnosability properties given a system model taking into account, both simultaneously or separately, integral and differential causal interpretations for differential constraints. We develop a model characterization and corresponding algorithms, for studying system diagnosability using a structural decomposition that avoids generating the full set of system ARRs. Simultaneous application of integral and differential causal interpretations for differential constraints results in a mixed causality interpretation for the system. The added power of mixed causality is demonstrated using a case study. Finally, we summarize our work and provide a discussion of the advantages of mixed causality over just derivative or just integral causality.

Erik Frisk, Anibal Bregon, Jan Åslund, Mattias Krysander, Belarmino Pulido and Gautam Biswas

21st International Workshop on Principles of Diagnosis (DX-10), 2010

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