Realizing On-Chip Digital Twin for Event Tracking in Squirrel Cage Induction Motors and Drives

In this paper, we present a comprehensive real-time simulator for a squirrel cage induction motor drive on a 32-bit processor, specifically utilizing the Raspberry Pi 4 Model B. Our approach involves coding a coupled circuit model that can handle a variety of faults, including both healthy and faulty conditions. The input to the system is provided from a three-phase voltage source, along with a load torque, while the output includes stator current, speed, and electromagnetic torque. By employing this model, we capture the dynamic behavior of the motor during starting transients and various fault scenarios, such as broken rotor bar fault, broken end ring fault, ball bearing fault, and eccentricity fault. The analysis focuses on monitoring and analyzing the current signatures, which serve as prime indicators for detecting faults and anomalies. The proposed real-time simulator seamlessly integrates into standard drive circuits, allowing for simultaneous fault diagnosis and prognosis during motor operation. Moreover, the module can be connected to the internet, enabling event tracking capabilities. Our work demonstrates the practicality and usefulness of real-time fault diagnosis and prognosis in squirrel cage induction motors, offering an effective approach for enhancing motor reliability and performance.