Batch Process Fault Diagnosis Based on Fuzzy Petri Nets

The fuzzy Petri net (FPN) is a new kind of Petri nets that is well developed in recent years. It is difficult to model and simulate the fault diagnosis of batch process because of the alternation between the discrete states and the continuous process. This paper concerned with a new method of complex batch process fault diagnoses based on fuzzy Petri nets. We use Petri nets to model batch processes, and use fuzzy probability to deal with the uncertain information in fault diagnoses and calculate the dependability in fault diagnoses. A simulation of the fault diagnosis system is illustrated with a batch process example, the conclusion of which shows that this method is feasible