基于粒子群算法的工件三维膨胀变形下转站参数优化  

Optimization of transfer station parameters of a laser tracker based on the particle swarm algorithm for a large part experiencing 3D deformation

作　　者：刘华森 陈恳[1] 王国磊[2] LIU Huasen;CHEN Ken;WANG Guolei(Department of Mechanical Engineering,Tsinghua University,Beijing 100084,China;State Key Laboratory of Tribology,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学机械工程系,北京100084 [2]清华大学摩擦学国家重点实验室,北京100084

出　　处：《清华大学学报（自然科学版）》2021年第9期979-985,共7页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金资助项目(51975308);工信部民机专项(MJZ-2018-G-75)。

摘　　要：大型航空产品工件受温度变化而膨胀变形等影响,这会对产品的精确数字化测量以及部件对接的精度产生重要影响。该文提出一种工件三维膨胀变形的激光跟踪仪转站参数优化方法,根据工件的三维数模,通过ANSYS有限元热分析计算工件初步热膨胀变形的中心点;建立考虑工件三维热膨胀变形的转站目标优化函数,对种群个体进行随机初始化赋值,并计算个体的适应值;采用粒子群优化算法(particle swarm optimization, PSO)对种群个体进行迭代优化,直到计算得到最优的跟踪仪转站参数。该方法充分考虑了大型工件受温度变化引起的工件三维热变形因素,提高了跟踪仪转站测量的精度。The shapes of large aviation workpieces can deform due to temperature changes, which significantly impacts precise digital measurements of the product shape and the accuracy of component docking. This paper describes a method to optimize the transfer station parameters of a laser tracker to account for three-dimensional deformation of the workpiece. The center of a three-dimensional model of the workpiece was calculated using the ANSYS finite element thermal analysis to account for the thermal expansion of the workpiece. An objective function was then defined for optimizing the transfer station parameters that considered the three-dimensional thermal expansion of the workpiece. Numerous individuals in a population of models were randomly initialized to calculate the adaptive values for each individual. The particle swarm optimization(PSO) algorithm was then used to iteratively optimize the individuals in the population to obtain the optimal tracking transfer parameters. This method takes into account the three-dimensional thermal deformation of large workpieces caused by temperature changes to improve the tracker measurement accuracy.

关 键 词：三维热膨胀 跟踪仪转站 参数优化 粒子群优化算法(PSO) 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]