Application of fuzzy data fusion theory in fault diagnosis of rotating machinery. (August 2018) - Jafari, Hamideh; Poshtan, Javad; Sadeghi, Hamed
In this article, the most common induction motor faults including bearing outer race defect, broken rotor bar, and short-circuit of stator windings are diagnosed with high reliability. The decentralized fuzzy-integral data fusion method is used for information fusion in feature level. In the proposed scheme, the feature vectors are constructed using signatures created by time-domain characteristics obtained from stator three-phase current measurements. Partial matching of each feature is calculated by the fuzzy c-mean classifier algorithm, and features with high diagnosis ability are fused by Choquet fuzzy integral. The technique is validated experimentally on the 4 hp induction motor of an electropump, and the results are presented.