Modeling and Simulating of Uncertain Quality Abnormity Diagnosis

There is much fuzzy uncertain information during the diagnosis of quality abnormity. The effective utilization model of that can provide important decision-making support. In this study, we consider three main types of fuzzy production rules, which can be used in fuzzy quality abnormity diagnosis problem and their presentation models are constructed by use of Fuzzy Reasoning Petri Nets (FRPNs). Considering of the graphic representation and logic structure of FRPNs, we propose the method for simulating model using Matlab toolbox state flow. By establishing a corresponding relationship between FRPNs rules and state flow block diagram, three simulating models for the three corresponding FRPNs’ basic structure are developed. Finally, we give an application case of the proposed model. Taking place truth degree data of FRPNs as input, the diagnosis process and results can be shown dynamically in the state flow simulating model under Matlab environment. The result illustrated that the method proposed can give reliable information for process maintenance and abnormal causes’ location.