The Use of a Modified Prony's Method to Detect the Airgap-Eccentricity Occurrence in Induction Motors

Induction motors airgap-eccentricity fault detection has attracted the interest of many researchers in last decades. The Discrete Fourier Transform (DFT) has been widely used for that purpose. However, DFT can only give meaningful information for stationary signals. In this paper, an efficient time-domain technique based on a modified Prony's method for the airgap-eccentricity fault detection in induction motors is presented in order to overcome the DFT problems. Using this technique, the apparent power, as processed signal, is divided into short overlapped time windows, and each one is analyzed by the Least Squares Prony's method. The proposed technique allows tracking the frequencies and amplitudes of the airgap-eccentricity fault characteristic frequency component f(r) with a very high accuracy. A fault severity factor (FSF) based on f(r) amplitudes is defined. Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method.