Fault detection and diagnosis in three phase IM using DSP: hardware implementation and real-time approach

Abstract

The study investigates real-time problem diagnosis of induction motors (IMs) with digital signal processing (DSP) to improve monitoring. IMs are essential to industrial applications but can fail owing to mechanical, electrical, and thermal stressors. These defects must be detected quickly to prevent motor failure and production downtime. DSP is used to create a sophisticated real-time online condition monitoring system to diagnose three-phase IM issues. The suggested system was validated using MATLAB calculations and experimental investigations on a 415 V, 1 HP, 50 Hz, 1440 rpm, 4-pole IM. Disruptions in the stator windings, such as inter-turn short circuits or inter-phase faults, as well as problems with the rotor, such as broken bars or end rings, are identified in this investigation. Keeping an eye on negative sequence currents and analyzing fault frequencies with a fast Fourier transform (FFT). According to the results of the testing, current approaches are not very good at detecting stator inter-turn difficulties under light-load and no-load conditions. Under varying loads, the proposed DSP-based system identified stator inter-turn, inter-phase, and broken rotor bar problems. Results showed that the DSP-based online condition monitoring system was more accurate and better at detecting faults than earlier methods, making it a good fit for usage in industrial applications.