摘要
为识别转子的不平衡参数,建立了转子-轴承有限元模型,在逆问题的识别理论基础上通过理论故障力与等效估计的不平衡力构建目标函数,运用果蝇优化算法进行目标函数优化,从而识别出不平衡参数,并将果蝇算法识别的结果与模拟退火算法、遗传算法的结果进行对比。仿真和实验结果均表明,相比其他两种算法,果蝇算法有更高的识别精度和效率。
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.
作者
刘亮
姚剑飞
高树成
杨伟
赵学茹
LIU Liang;YAO JianFei;GAO ShuCheng;YANG Wei;ZHAO XueRu(College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology,Beijing 100029,China)
出处
《北京化工大学学报（自然科学版）》
CAS
CSCD
北大核心
2018年第3期79-83,共5页
Journal of Beijing University of Chemical Technology(Natural Science Edition)
基金
中央高校基本科研业务费(JD1713)
关键词
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
