The intelligent fault diagnosis frameworks based on fuzzy integral

Abstract

Fuzzy integral is an information aggregation and combination process in a multi-criteria environment using fuzzy measures. This paper presents a new data fusion method using fuzzy integral for fault diagnosis. The method consists of two frameworks. The first framework was employed to identify the relations between features and a specified fault. The second framework was implemented to integrate different diagnosis algorithms to improve the accuracy rates of them. The choquet fuzzy integral was utilized for two frameworks. The proposed approach was experimentally implemented on a 0.37 kW induction motor. Broken rotor bar and stator faults were evaluated to validate the models. The results showed that the proposed method performs very well for broken rotor bar and stator faults. © 2010 IEEE.