基于粒子群算法的深沟球轴承优化设计  

Optimal Design of Deep Groove Ball Bearings Based on Particle Swarm Optimization

作　　者：李敬雍 高飞 黄利平[1] 田凌[1] LI Jingyong;GAO Fei;HUANG Liping;TIAN Ling(Department of Mechanical Engineering,Tsinghua University,Beijing 100084,China;Luoyang Bearing Research Institute Co.,Ltd.,Luoyang 471039,China)

机构地区：[1]清华大学机械工程系,北京100084 [2]洛阳轴承研究所有限公司,河南洛阳471039

出　　处：《轴承》2023年第1期12-16,27,共6页Bearing

基　　金：国家自然科学基金资助项目(51675299)。

摘　　要：以深沟球轴承的额定动载荷、额定静载荷及额定联合载荷为优化目标,以球直径、球组节圆直径、球数、内圈沟曲率半径系数、外圈沟曲率半径系数为设计变量,基于粒子群算法实现了轴承的主参数优化。同时,基于.NET API对AutoCAD软件进行二次开发,实现轴承二维图纸的自动绘制与保存。以6214深沟球轴承为例进行优化设计,优化过程收敛速度快且收敛稳定性高;与网格节点法的优化结果对比表明,基于粒子群算法优化设计后的轴承额定动载荷更高。Taking dynamic load rating,static load rating and combined load rating of deep groove ball bearings as optimization objectives,taking ball diameter,pitch diameter of ball set,ball number,groove curvature radius coefficient of inner ring and groove curvature radius coefficient of outer ring as design variables,the main parameters of the bearings are optimized based on particle swarm optimization.At the same time,the second development of AutoCAD software is carried out based on.NET API to realize the automatic drawing and saving of bearing two-dimensional drawings.Taking 6214 deep groove ball bearing as an example for optimal design,the optimization process has fast convergence speed and high convergence stability.Compared with optimal results obtained by grid node method,the bearing after optimal design based on particle swarm optimization has higher dynamic load rating.

关 键 词：滚动轴承 深沟球轴承 优化设计 额定载荷 粒子群算法 

分 类 号：TH133.331[机械工程—机械制造及自动化] O224[理学—运筹学与控制论]