摘要
在机翼大部件数字化装配过程中,由于大型机翼的位姿通常是通过调姿基准点的理论位置与实际位置的匹配来评价的,而其装配变形也通过基准点的位置误差来表示,因此合理的基准点位置对于机翼的数字化装配具有重要意义。本文提出了一种基于自适应离散粒子群算法的基准点优化布局方法,该方法能够包含更多的机翼变形信息,从而有效地描述装配误差。最后通过一个例子说明,利用最大化费希尔信息矩阵的行列式的值,从较大的候选基准点中选择最优的基准点集,并与经典离散粒子群算法的优化结果进行了比较,说明了前者的寻优效果更好。
In the process of digital assembly of large wing components, the position and attitude of large wings are usually evaluated by the matching between the theoretical position and the actual position of the attitude adjustment reference point, and the assembly deformation is also expressed by the position error of the reference point, so the reasonable position of the reference point is of great significance for the digital assembly of the wing.In this paper, a reference point optimization layout method based on adaptive discrete particle swarm optimization algorithm is proposed, which can contain more wing deformation information and effectively describe the assembly error. Finally, an example is given to illustrate that the optimal set of reference points is selected from the larger candidate datum points by maximizing the determinant of Fisher information matrix, and the optimization results are compared with those of the classical discrete particle swarm optimization algorithm. the results show that the optimization effect of the former is better.
作者
高井涛
郑子君
Gao Jingtao;Zheng Zijun(Nanchang Hangkong University,School of Aeronautical Manufacturing Engineering,Nanchang 330063,China)
出处
《科学技术创新》
2022年第11期41-44,共4页
Scientific and Technological Innovation
关键词
优化布局
自适应离散粒子群算法
费希尔信息矩阵
数字化装配
Optimal layout
Adaptive discrete particle swarm algorithm
Fisher information matrix
Digital assembly
