Diagnosis of Multiple Short-Circuit Faults in Three-Phase Induction Motors Using Electric Phasor Analysis of Line Currents and Fuzzy Logic

The three-phase induction motor (IM) plays an essential role in industry; therefore, ensuring these motors operate under faultless and reliable conditions. Previous studies have reported that 28% to 38% of IM failures are related to the stator windings. For this reason, numerous efforts have been made to develop low-cost procedures for early fault detection in IMs. However, their primary drawback is that they involve complex mathematical operations for analyzing acquired information in the frequency or time-frequency domains, making online implementation challenging. Consequently, there remains a need for a reliable, online method to detect faulty conditions in IMs. In this work, a straightforward methodology based on the phasor-representation analysis and a fuzzy logic classifier is proposed for the online detection and classification of short-circuit faults in a three-phase IM. The signal-processing technique in this approach involves basic arithmetic operations, making it feasible for implementation on the Texas Instruments 32-bit, floating-point digital signal processor TMS320F28335. The obtained results demonstrate the efficacy and utility of the proposed methodology in detecting and classifying incipient or simultaneous short-circuit faults. It significantly reduces processing time while achieving high precision and accuracy compared to previous approaches reported in recent literature.