Induction Motors Faults Identification Using Frequency Response Analysis Framework

The three-phase induction motors (TPIMs) are widely used in industrial power systems due to their robustness and efficiency. However, undetected electrical or mechanical faults can lead to costly downtime and performance degradation. This paper proposes a non-destructive method for early fault detection in TPIMs, using a frequency response analysis (FRA) framework. An equivalent RLC circuit model of the stator windings is created in MATLAB/Simulink to analyze the impedance characteristics of the motor in healthy and faulty conditions. By systematically changing the resistance (R), inductance (L), and capacitance (C), the model produces different frequency response characteristics, highlighting deviations in the lowfrequency (LF), mid-frequency (MF), and highfrequency (HF) regions. This paper proposes a fault severity index to quantify these deviations and classify the motor's health status. The results show that resistance changes affect all frequency ranges, inductance mainly affects the mid-frequency region, and capacitance changes mainly affect the highfrequency region. The results demonstrate that the proposed FRA-based method can achieve accurate, scalable, and non-invasive fault diagnosis, providing an effective alternative to traditional, often timeconsuming and labor-intensive detection techniques.