为了提高装配的精度,可以使用计算机辅助选择装配来选择合适的零件进行装配。提出了一种面向多尺寸链计算机辅助选择装配模型;对比了几种多目标优化算法应用在计算机辅助选择装配中的优缺点;最终选择一种以粒子群优化算法为基础的多目标优化算法,在算法中通过使用外部集的不断更新来保证算法收敛到全局最优解。实例证明,随着迭代次数的增加,外部集中的解逐渐收敛于pareto前沿,而且解的分布比较均匀。
In order to improve the precision of assembly,Computer Aided Selective Assembly can achieve this target.This article proposes a new selective assembly model used in muhi-dimension chains and contrasts different multi-object optimization algorithms when they are applied on Computer Aided Selective Assembly.Based on PSO,an improved PSO algorithm is designed to solve the problem of multi-objective optimization.In the improved algorithm,authors use an external collection to update the solutions,assure the algorithm can better converge near the tree Pareto-optimal front and ensure the distributing of solutions is better equality.Finally,a fact proves that this model and algorithm can efficiently. solve the selective assembly problem.