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Component Models Based Approach for Failure Diagnosis of Discrete Event Systems
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Author(s): Alexandre Philippot (Université de Reims Champagne-Ardenne, France), Moamar Sayed-Mouchaweh (Université de Reims Champagne-Ardenne, France)and Véronique Carré-Ménétrier (Université de Reims Champagne-Ardenne, France)
Copyright: 2010
Pages: 23
Source title:
Intelligent Industrial Systems: Modeling, Automation and Adaptive Behavior
Source Author(s)/Editor(s): Gerasimos Rigatos (Industrial Systems Institute & National Technical University of Athens, Greece)
DOI: 10.4018/978-1-61520-849-4.ch016
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Abstract
This chapter addresses the problem of diagnosing Discrete Event Systems (DESs), specifically manufacturing systems with discrete sensors and actuators. Manufacturing systems are generally composed of several components which can evolve with the course of time (new components, new technologies …). Their diagnosis requires the computation of a global model of the system. This is not realistic due to the great number of components. In this chapter, we propose to perform the diagnosis by using component models. Each component model is constructed using different information sources represented by sensor-actuator spatial structure (plant model), controller specifications (desired behaviour) and temporal information about the actuators reactivity. In addition, components’ technological constraints and characteristics are considered for this construction. For each model, a local diagnoser is computed. Its complexity is polynomial because the diagnosis is computed only for the faults that it can diagnose. Limited information about the global system functioning is required to synchronize the functioning of local diagnosers. This synchronisation is considered using a set of expert rules representing the symbolic information about the global desired behaviour. The local diagnosers are then used to perform diagnosis online. They validate, in the case of normal functioning, the transmission of control signals and incoming sensor data between the controller and the plant.
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