摘要
根据最小区域条件,建立了圆柱度误差的数学模型以及优化目标函数和适应度函数,阐述了粒子群优化算法的原理和实现方法,然后根据粒子群算法优化求解。实例表明,该方法对于圆柱度误差评定等非线性优化问题能得到全局最优解,粒子群优化算法的计算精度与其他满足最小条件的计算方法相比略有提高,且参数设置少,计算速度快,可用于三坐标测量机等测量系统的圆柱度误差测量后的数据处理。
A method of evaluation cylindricity errors based on particle swarm optimization （PSO） was proposed. According to the minimum zone condition, a mathematical model of cylindricity errors together with the optimal objective function and fitness function was developed. The principle and implementation techniques of PSO were introduced. Then the particle swarm optimization algorithm was used to search for the optimal solution. Finally the example showed that PSO method is suitable for the nonlinear optimization problems such as cylindricity error evaluations. In addition, the precision of PSO is better than other methods under minimum zone condition. Thus PSO has the advantages of setting up a few parameters and a rapid convergent velocity. So it can be applied in dealing with the-measured data of cylindricity obtained by three-coordinate measuring machine （CMM）.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2007年第2期146-149,共4页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金资助项目(项目编号:50275136
50505046)
关键词
圆柱度
误差评定
粒子群算法
Cylindricity, Error evaluation, Particle swarm optimization algorithm
