Diagnosis of Active Systems by Semantic Patterns

A gap still exists between complex discrete-event systems (DESs) and the effectiveness of the state-of-the-art diagnosis techniques, where faults are defined at component levels and diagnoses incorporate the occurrences of component faults. All these approaches to diagnosis are context-free, in as much diagnosis is anchored to components, irrespective of the context in which they are embedded. By contrast, since complex DESs are naturally organized in hierarchies of contexts, different diagnosis rules are to be defined for different contexts. Diagnosis rules are specified based on associations between context-sensitive faults and regular expressions, called semantic patterns. Since the alphabets of such regular expressions are stratified, so that the semantic patterns of a context are defined based on the interface symbols of its subcontexts only, separation of concerns is achieved, and the expressive power of diagnosis is enhanced. This new approach to diagnosis is bound to seemingly contradictory but nonetheless possible scenarios: a DES can be normal despite the faulty behavior of a number of its components; also, it can be faulty despite the normal behavior of all its components.