Rapid Control Prototyping and Analysis of a Fault Diagnosis and Amplifying Algorithm for Broken Rotor Bar Induction Motor Drives

This paper introduces a sensitivity-enhanced fault detection algorithm, termed the Fault Diagnosis and Amplifying (FDnA) method, designed to amplify fault signals in induction motors with broken rotor bars. The FDnA algorithm employs a cascaded state observer structure, integrating stator flux linkage and stator current observers based on an analytical model of an induction motor. By multiplying the output signals of these observers, the algorithm significantly enhances the sensitivity of fault detection. The FDnA method is robust against external environmental conditions and excels in accurately detecting broken rotor bar faults. Additionally, it offers a cost-effective and retrofittable solution by replacing traditional sensors and interfacing circuits with state observers, eliminating the need for additional hardware. Comprehensive validation through simulations and rapid control prototyping highlights the superior fault detection sensitivity of the FDnA method compared to conventional approaches, establishing it as a reliable and efficient advancement in fault detection for induction motors.