基于响应面法的小孔节流静压气体轴承多目标优化  

Multi-objective Optimization of Aerostatic Bearing with Orifice Based on Response Surface Method

作　　者：邱春雷 尹洋[1] QIU Chunlei;YIN Yang(School of Mechanical Engineering,Xihua University,Chengdu Sichuan 610039,China)

机构地区：[1]西华大学机械工程学院,四川成都610039

出　　处：《润滑与密封》2022年第7期125-130,共6页Lubrication Engineering

基　　金：四川省科技厅重点研发项目(2017GZ0356);西华大学研究生创新基金项目(YCJJ2021051)。

摘　　要：以小孔节流静压气体轴承为研究对象,针对其承载力和刚度较低、质量流量较大的缺点,运用响应面设计方法全面分析节流器参数对轴承性能的影响以及参数间的交互影响,得到拟合公式用于预测目标函数,并以最大承载力、最大刚度和最小质量流量为设计目标,采用精英策略的多目标遗传算法优化轴承性能。研究表明:节流器参数对轴承性能的影响极显著,同时,参数间的交互作用对目标函数均有影响;节流孔直径是承载力和质量流量的显著交互影响参数,偏心率是刚度的显著交互影响参数。得到的二阶多项式拟合公式可以近似计算轴承性能,可用于预测目标函数。采用多目标优化使轴承承载力提高57.1%,刚度提高50.2%,质量流量减少40%,显著提高了轴承性能。Taking the aerostatic bearing with orifice restrictors as the research object,aiming at the shortcomings of low bearing capacity and stiffness and large mass flow,the response surface design method was used to comprehensively analyze the influence of restrictor parameters on bearing performance and the interaction between parameters.The fitting formula was obtained which can be used to predict the objective function.Taking the maximum bearing capacity,the maximum stiffness and the minimum mass flow as the design objectives,the multi-objective genetic algorithm with elite strategy was used to optimize the bearing performance.The results show that the influence of restrictor parameters on bearing performance is very obvious,and the interaction between parameters has impact on the objective function.Orifice diameter is the dominant interaction parameter of bearing capacity and mass flow,eccentric ratio is the dominant interaction parameter of stiffness.The obtained second-order polynomial fitting formula can approximate the bearing performance and can be used to predict the objective function.After multi-objective optimization,the bearing capacity is increased by 57.1%,the stiffness is increased by 50.2%,and the mass flow is reduced by 40%,which significantly improves the bearing performance.

关 键 词：静压气体轴承 响应面法 遗传算法 多目标优化 

分 类 号：TH133.35[机械工程—机械制造及自动化]