Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems. Faults and degradations need to be quickly identified so that corrective actions can avoid catastrophic situations. Most real-world, embedded systems are hybrid in nature. In such systems, hybrid models have to be employed for correct tracking and diagnosis. The majority of hybrid systems diagnosis work, however, has focused on either discrete or parametric fault diagnosis. In contrast, we present an integrated model-based approach to diagnosing both parametric and discrete faults in hybrid systems. This extends our previous work in diagnosis of parametric faults in hybrid systems [1,2] by including discrete faults, resulting in a unified hybrid diagnosis methodology. We demonstrate our approach using experimental results performed on a complex electrical power system.
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