Incipient Stator Winding Turn Faults Detection in Induction Motor

Developed countries consume over 70% of the generated electricity by electric motors, while over 90% of these motors are induction motors. Therefore, induction motors are core element for any industry. The used motors are subject to various faults which might cause enormous consequences. Incipient fault is one of the hardest faults to detect, which also grows with time, then at a certain point, the motor breaks down without prior warning. This research aims to develop an online detection system that detects the stator winding inter-turn fault explicitly and identifies the severity of the stator winding fault. The inter-turn fault happens when a short circuit occurs between wires that are close to each other in the stator winding, due to a lot of factors such as high temperature or motor overloading. The three-phase stator current signal data collected is analyzed using discrete wavelet transform method. Then, the power spectral density (PSD) method is utilized to extract the three-phase stator current signals to obtain the frequency spectrum of stator currents. A Finite Element Analysis (FEA) model of the induction motor with the stator winding turn fault is presented. In addition, an experimental set-up is built for validating the proposed detection system. Simulation and experimental results are curried out to demonstrate the effectiveness of the proposed methodology.