Analysis of Multiple Broken Rotor Bar Fault in Induction Motor

Abstract

Induction motors are widely used in industrial applications due to their durability, simplicity, and low cost. They are, however, susceptible to a variety of faults during operation, one of the most critical of which are broken rotor bar (BRB) faults, which have the potential to cause severe performance degradation and unexpected downtime. This study describes an effective diagnostic approach for detecting BRB faults using Motor Current Signature Analysis (MCSA). The Fast Fourier Transform (FFT) was used to extract the fault-related features and the Hann’s windowing function was used to minimize the spectral leakage caused by the non-stationary nature of the stator current signal. The experimental stator current data was taken for healthy and faulty motor (BRB) conditions at different load conditions. The frequency domain analysis showed distinct sideband components whose characteristics varied according to fault severity and loading. Additionally, motors under full load revealed more defined spectral features, making fault detection more reliable. The findings demonstrate that this FFT-based approach, enhanced by appropriate windowing, provides an effective and non-invasive solution for early detection of rotor faults in an induction motor.