摘要
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,应用粒子群算法对该模型进行优化。研究了粒子群算法中搜索步长、粒子数和迭代次数3个主要参数对动压滑动轴承优化设计结果的影响,提出了确定需要考虑的主要方面,即根据约束条件的数量确定合适的搜索步长、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粒子数和根据粒子收敛的情况确定合适的迭代次数。算例表明,文中提出的在动压滑动轴承优化设计中对粒子群算法参数的选择是合理的,可以拓展到基于粒子群算法进行优化设计的其他领域。
Based on the objective function to reduce the flowrate of lubricating oil, the model of optimization design of dynamicjournal bearing was established and optimized by the particle swarm algorithm. The effect on the results of optimization design of dynamic journal bearing by the searching step,particle number and iteration number of particle swarm algorithm was studied, and the main aspects need to be considered in determining appropriate searching step by the number of constraint conditions, appropriate particle number by the characteristic of optimization model and the complexity of constraint condition and appropriate iteration number by the situation of particle convergence were presented. The results show that the determination method used in choosing the parameter of particle swarm algorithm in the optimization design of dynamic journal bearing presented in this paper is reasonable and can be expanded to other field of optimization design based on particle swarm algorithm.
出处
《机械设计》
CSCD
北大核心
2014年第3期55-59,共5页
Journal of Machine Design
关键词
动压滑动轴承
优化设计
粒子群算法
算法参数选择
dynamic journal bearing
optimization design
particle swarm algorithm
algorithm parameter choice
