Observable Simple Temporal Network synthesis for the diagnosis of time patterns in time Petri nets

This paper presents a method for the diagnosis of time patterns in time Petri nets. This method uses a characterization of the pattern called Observable Simple Temporal Network, given in the form of a set of observable events with temporal constraints on their occurrence dates. The proposed diagnoser verifies if a part of an input timed sequence of observations is consistent with the characterization. If the pattern has not occurred, this consistency test will lead to the same conclusion. One the other hand, if the pattern has occurred, the consistency test will lead to an ambiguous diagnosis in the general case or to the conclusion that the pattern has definitely occurred if the underlying system is diagnosable.