Title :
Fault Diagnosis Graph of time Petri nets
Author :
Xu Wang ; Mahulea, Cristian ; Silva, M.
Author_Institution :
Inst. de Investig. en Ing. de Aragon (I3A), Univ. de Zaragoza, Zaragoza, Spain
Abstract :
This paper proposes an online approach for the fault diagnosis for time discrete event systems, which are modeled by time Petri net. The observation is given by a subset of transitions whose occurrence is always observable. Faults correspond to a subset of the transitions whose firing are not observable. According to the most of the literature on discrete event systems, we define three fault states, namely N, F and U, corresponding to normal, fault and uncertain states, respectively. The proposed approach use a Fault Diagnosis Graph (FDG). It is adapted from state class graph by keeping only the necessary information for computation of the fault states and removing the unnecessary states. Some algorithms to compute after each observation only part of the FDG required to update the diagnosis states are given.
Keywords :
Petri nets; discrete event systems; fault diagnosis; graph theory; FDG; fault diagnosis graph; state class graph; time Petri nets; time discrete event systems; Artificial neural networks; Computational modeling; TV;
Conference_Titel :
Control Conference (ECC), 2013 European