动压滑动轴承遗传算法优化设计中的参数选择  

Parameter choice in optimization design of hydrodynamic journal bearing based on genetic algorithms

作　　者：舒磊[1] 王晓红[2] 孙军[1] 宋现浩 许枫[1] 

机构地区：[1]合肥工业大学机械与汽车工程学院,安徽合肥230009 [2]中国船舶重工集团公司第七0三研究所,黑龙江哈尔滨150078

出　　处：《合肥工业大学学报（自然科学版）》2015年第8期1028-1032,共5页Journal of Hefei University of Technology：Natural Science

基　　金：合肥工业大学产学研校企合作资助项目(11-680)

摘　　要：文章建立了以降低润滑油流量为目标的动压滑动轴承优化设计模型,应用遗传算法对该模型进行优化;研究了遗传算法中位串长度、种群个体数、进化代数和变异概率4个主要参数对动压滑动轴承优化设计的影响,并提出了根据约束条件的数量确定合适的变异概率,根据优化模型自身特点和约束条件的复杂程度确定合适的位串长度、种群个体数和变异概率,根据种群收敛的情况确定合适的进化代数。算例表明,文中提出的动压滑动轴承遗传算法优化设计中参数的选择确定方法是合理的,可以拓展到基于遗传算法进行优化设计的其他领域。The optimization design model of hydrodynamic journal bearing for reducing oil flow-rate was established and optimized by the genetic algorithms. The effects of the string length, population size, evolution generation and mutation probability in genetic algorithms on the optimization design of hydrodynamic journal bearing were researched. The appropriate mutation probability was determined based on the number of constraint condition, the appropriate string length, population size and muta- tion probability were determined based on the model characteristics and the complexity of constraint condition, and;the appropriate evolution generation was determined based on the situation of population convergence. ＂The example result shows that the presented method to determine the parameter choice in the optimization design of hydrodynamic journal bearing based on genetic algorithms is reasonable and can be extended to other fields of optimization design based on genetic algorithms.

关 键 词：动压滑动轴承 优化设计 遗传算法 算法参数 

分 类 号：TH133.31[机械工程—机械制造及自动化]