Model-Based Fault Detection and Diagnosis of Slip-Ring Induction Motors: A Simulation Study

In this paper, a new non-invasive model-based fault detection and diagnosis of stator and rotor inter-turn faults in slip ring induction motors (SRIMs) are presented. Analytical modeling of SRIM with electrical faults is formulated. Innovation sequence generated from extended Kalman filter is used for accurate fault detection. Further, fault diagnosis is carried out using Brute-force search algorithm. Simulation results show that the presented method is an effective diagnosis procedure for major electrical faults in SRIMs. Robustness towards supply imbalance and speed varying conditions are the significant advantages of the proposed strategy