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Keywords Abstract

-  2018 


DOI: 10.13543/j.bhxbzr.2018.03.012

Keywords: 转子不平衡,参数辨识,逆问题,果蝇算法,
rotor unbalance
,parameter identification,inverse problem,fruit fly algorithm

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Abstract:In order to identify the rotor unbalance parameters of a rotor, a finite element model of the rotor bearing system was established. The objective function, derived from the difference between theoretical loads and the estimated equivalent unbalance forces based on inverse problem theory, was optimized by using a fruit fly algorithm. Parameters were identified when the objective function reached its minimum. The results of the fruit fly algorithm identification were compared with the results identified by the simulated annealing algorithm and the genetic optimization algorithm. The simulation and experimental results show that the fruit fly algorithm is a more accurate and efficient way for identifying unbalance parameters than the remaining other two algorithms.


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