Fault Diagnosis for Time Petri Nets

Abstract

This paper presents an on-line algorithm for fault diagnosis of time Petri net (TPN) models. The plant observation is given by a subset of transitions whose occurrence is always reported while the faults are represented by unobservable transitions. The model-based diagnosis uses the TPN model to derive the legal traces that obey the received observation and then checks whether fault events occurred or not. To avoid the consideration of all the interleavings of the unobservable concurrent transitions, the plant analysis is based on partial orders (unfoldings). The legal plant behavior is obtained as a set of configurations. The set of legal traces in the TPN is obtained solving a system of (max,+)-linear inequalities called the characteristic system of a configuration. We present two methods to derive the entire set of solutions of a characteristic system, one based on extended linear complementarity problem and the second one based on constraint propagation that exploits the partial order relation between the events in the configuration