Shuguang Wei, Jiaqi Li*, Zixu Zhao, Dong Yuan
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1035-1052, 2022, DOI:10.32604/cmc.2022.024201
Abstract This paper proposes an artificial neural network for monitoring and detecting the eccentric error of synchronous reluctance motors. Firstly, a 15 kW synchronous reluctance motor is introduced and took as a case study to investigate the effects of eccentric rotor. Then, the equivalent magnetic circuits of the studied motor are analyzed and developed, in cases of dynamic eccentric rotor and static eccentric rotor condition, respectively. After that, the analytical equations of the studied motor are derived, in terms of its air-gap flux density, electromagnetic torque, and electromagnetic force, followed by the electromagnetic finite element analyses. Then, the modal analyses of the… More >
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