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

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This paper presents a wavelet based prognosis techniques for fault tolerant control (FTC) of induction motor drive. The wavelet is used for analysis in fault detection due to its good filtering characteristics, localized capability and superior de-noising. The FT algorithm is applied to a 1 kW induction motor (IM) to maintain the performance of the machine at an acceptable level. The FTC algorithm has been implemented in a new topology to ensure best performance recovery in case of open and short stator winding faults as well as speed sensor faults. In the worst 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 IM drive under different fault situations.