Uncertain quality abnormity diagnosis by stateflow-based simulating of Fuzzy Reasoning Petri Nets Model: A case study

Abstract

Fuzzy Reasoning Petri Nets (FRPNs) has been used widely to deal with fuzzy uncertain information in fault diagnosis. But for its particular graphic representation and logic structure, it is hard to simulate and analyze the process of abnormity producing and spreading dynamically. In this study, a stateflow-based method has been investigated for simulating FRPNs Model of uncertain quality abnormity diagnosis. In this method, elements of stateflow diagram, such as state, transition, state action and marking label of transition, are used to represent the place, directed arc and transition rules of FRPNs respectively. According to the transition relation and monitoring logic, stateflow-based simulating model of FRPNs was constructed by use of above elements. Fired by control chart data, the model can analyze the occurrence degree of abnormity pattern in control chart, show the diagnosis process dynamically and finally give the diagnosis result. The result illustrated the effectiveness of the proposed method.