Case-based reasoning system with Petri nets for induction motor fault diagnosis

摘要

This paper presents an innovative approach for integrating case-based reasoning (CBR) with Petri net for the fault diagnosis of induction motors. In the CBR system, maintenance engineers can retrieve the information from previous cases which closely resemble the new problem and solve the new problem using the information from the previous cases. The proposed system has been used in fault diagnosis of electric motor to confirm the system performance. The result shows the proposed system performs better than the conventional CBR system.