Bearing fault detection via Park´s vector approach based on ANFIS

In this paper, Park´s vector transformation and frequency domain analysis for fault detection of induction motors are introduced. Then a smart approach based on Adaptive Nuero Fuzzy Inference System (ANFIS) that uses time domain features obtained from the Park´s transformation of stator currents is proposed for fault detection. By the proposed method, a 1 mm hole on the inner race and two faults including 1 mm and 3 mm hole on the outer race, using experimental data is investigated. It is shown that using features derived from Park´s vector modulus results in better performance compared to the features obtained from a single phase current.