A Symmetrical Components-based Load Oscillation Detection Method for Closed-Loop Controlled Induction Motors

This paper investigates the use of instantaneous symmetrical components (ISCs) for mechanical faults detection in inverter-fed induction motors under closed-loop control. The proposed fault detection approach is based on the computation of the ISCs of the stator currents. The positive sequence power spectral density (PSD) is estimated using ESPRIT and least squares (LS). Then, mechanical fault detection is considered as a binary hypothesis test and solved using the generalized likelihood ratio test (GLRT). Both stator currents and the modulating signals issued from the control-loops are demonstrated to be efficient for fault detection. Simulation results on an analytical model of an inverter-fed induction motor illustrate the effectiveness of the proposed approach, leading to an effective fault detection procedure for load torque oscillation in inverter-fed induction motor under closed-loop operation.