Induction Motor Faults Detection Using a Statistical Procedure Based-Approach

Abstract

This paper presents the application of a new technique based on the variance of three phase stator currents’ instantaneous variance (VIV-TPSC) to detect faults in induction motors. The proposed fault detection algorithm is based on computation of the confidence interval index (CI) at different load conditions. This index provides an estimate of the amount of error in the considered data and determines the accuracy of the computed statistical estimates. The algorithm offers the advantage of being able to detect faults, particularly broken rotor bars, independently of loading conditions. Moreover, the implementation of the algorithm requires only the calculation of the variance of the measured three-phase stator currents’ instantaneous variance. The discrimination between faulty and healthy operations is based on the adherence of VIV-TPSC value to the CI which is calculated after checking out that the variance of instantaneous variance is a random variable obeying to normal distribution law. Rotor and stator resistance values are not used in any part of the CI and VIV-TPSC calculations, giving the algorithm more robustness. The effectiveness and the accuracy of the proposed approach are shown under different faulty operations.