Modular Modeling for the Diagnostic of Complex Discrete-Event Systems

For the complex systems, the development of a methodology of fault diagnosis is important. Indeed, for such systems, an efficient diagnosis contributes to the improvement of the availability, the growth of production, and, of course, the reduction of maintenance costs. It is a key action in the improvement of performance of industrial feature. This paper proposes a new approach to diagnose complex systems modeled by communicating timed automata. Each component has been modeled separately by a timed automaton integrating various operating modes while the communication between the various components is carried out by the control module. Starting from each module of the complex system, a single deterministic automaton, called a diagnoser, is constructed that uses observable events to detect the occurrence of a failure. This modeling formalism provides means for formal verification of the complex system model and its diagnoser. The model-checking methods are used to check correctness properties. The steps of the method are described by an algorithm and illustrated through a batch neutralization process. The implementation of the algorithm is also discussed.