Fault detection/monitoring using time Petri nets

While controlling manufacturing systems, real time data is collected through sensory devices or some other means and fed back to the controller for the purpose of monitoring that system. Monitoring refers to the analysis of data collected from the system. It involves fault detection and diagnostics. Here, we shall emphasize the fault detection aspects of monitoring. Modeling the control system by a time Petri net permits us to develop an analytical procedure for fault detection. By backfiring transitions in the time Petri net, we are able to determine if a given state is invalid. The back-firing approach also provides us with state space representation of time Petri nets and the maximum token holding times in different places of time Petri nets