Wavelet-based prognosis for fault-tolerant control of induction motor with stator and speed sensor faults

Abstract

This paper presents a wavelet-based prognosis technique for fault-tolerant control (FTC) of an induction motor (IM) drive. The wavelet is used for analysis in fault detection due to its good filtering characteristics, localized capability and superior de-noising. The fault-tolerant algorithm is applied to a 1-kW IM to maintain the performance of the machine at an acceptable level. The FTC algorithm has been implemented in a new topology to ensure the best performance recovery in case of open and short stator winding faults, as well as speed sensor faults. In the worst-case scenario of operation, a protection stage has been implemented to stop motor operation. Experimental results demonstrate the reliability and effectiveness of the technique for diagnosis and prognosis of stator and speed sensor faults. The Texas Instrument TMS 320F28335 is used for the real-time implementation of the proposed wavelet-based prognosis and the FTC of the IM drive under different fault situations.