粒子群-蚁群融合算法在曝气机减速器优化设计中的应用  

Application of Particle Swarm Optimization and Ant Colony Optimization integration in the Aerator Reducer Optimization Design

作　　者：吴冬敏[1] 芮延年[1] 沈铭[1] 

机构地区：[1]苏州大学机电工程学院,江苏苏州215021

出　　处：《机械传动》2015年第1期158-161,共4页Journal of Mechanical Transmission

摘　　要：为了解决蚁群算法中参数的选取较大地依赖于实验者的个人经验,存在未成熟收敛的缺陷。提出一种PAAA算法对曝气机减速器行星轮系传动机构优化设计。在满足结构、强度等约束条件下,以行星轮系体积最小、效率最高为目标函数,建立行星轮系传动机构优化设计数学模型,再运用PAAA算法编写Matlab程序对所建数学模型进行求解。研究结果表明,在保证设计要求的条件下,行星轮系传动机构体积更小,效率更高。求解结果验证了PAAA优化方法快速有效,准确可靠。The Ant colony algorithm has the defects of premature convergence as its parameter se- lection greatly dependent on the personal experience. In order to solve the problem, a PAAA algorithm to optimization design the planetary gear reducer of the aerator is presented. To meet the constraints condition of structure and strength, taking the minimum volume and the highest efficiency of the plane- tary gear train as objective functions, its optimization mathematics model is established. The Matlab program is wrote to solve the mathematical model by using PAAA algorithm. The research results show that planetary gear train has smaller volume and higher efficiency under assuring the design requirements. The results also verified the PAAA optimization has the advantage of effective, accurate and reliable.

关 键 词：行星减速器 粒子群算法 蚁群算法 PAAA算法 优化设计 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TH132.46[自动化与计算机技术—控制科学与工程]