Fuzzy Petri Nets Reasoning for Application of Electric Control System Fault Diagnosis

In order to deal with the condition of inadequate and uncertain information in the fault diagnosis process of electric control system, fuzzy Petri net (FPN) reasoning model is investigated and developed. Based on fuzzy production rule, the improved fuzzy Petri net reasoning model is achieved by matrix parallel computation, and existing diagnosis knowledge are combined together to form a function matrix that is used to describe transfer of places and transitions in the fuzzy Petri net. Analytic hierarchy process (AHP) is employed to determine the initial certainty factor for intermediate places, which allows multiple objective factors to be considered in the fuzzy Petri net reasoning model. Matrix based fuzzy Petri net reasoning process is deduced and application example is used to validation the method. The proposed fuzzy Petri net reasoning model has the characteristics of easy establishment and high efficiency, and fault transition status within system can be described clearly