Current Sensor Fault Diagnosis for Induction Motor in Vector Control System

doi:10.16182/j.issn1004731x.joss.201808039

Abstract

Abstract: A current sensor fault diagnosis method of induction motor in vector control system is proposed. A state-space form including sensor faults and environmental disturbances/noises of induction machine is described. An augmented observer is designed to simultaneously estimate system states, and current sensor faults. To attenuate the effects from the environmental disturbances/noises, a genetic algorithm is employed to design observer gain by minimizing the estimation error against environmental disturbances and noises. A simulation model based on Matlab and real-data of the induction motor collected by experiment is utilized to validate the proposed methods, which show the efficiency of the proposed sensor fault diagnosis approaches. The proposed methods have great potential to improve the reliability of the real-time operation of the induction motor drive systems.

Key words: fault diagnosis, state estimation, genetic algorithm, sensor fault, induction motor, vector control, augmented observer

CLC Number:

TM346

Sun Kai, He Baina, Sarah Odofin, Gu Yu. Current Sensor Fault Diagnosis for Induction Motor in Vector Control System[J]. Journal of System Simulation, 2018, 30(8): 3139-3145.

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