Stator Winding Interturn Short-Circuit Fault Modeling and Detection of Squirrel-Cage Induction Motors

In this article, an interturn short-circuit (ITSC) fault detection method is presented based on the wavelet packet decomposition (WPD) and locus of three-phase currents in 3-D space for squirrel-cage induction motors (SCIMs). The proposed method is able to accurately identify the fault severity and location under any load condition and any type of motor power supply. A comprehensive dynamic model is also proposed for SCIMs having ITSC fault in one phase or a combination of multiple phases. The proposed signal-based fault detection method is separately evaluated based on the data extracted from the proposed model, the finite-element method (FEM), and the experimental test rig, which consists of two 1.5-kW induction motors, a 3-kW self-excitation generator, three LA55-P/SP1 Hall effect current sensors, a TMS320F28379D digital signal processor (DSP), and an electric drive system. The efficacy of the proposed fault detection method is evident from the results.