数字孪生环境下飞机装配过程中的激光跟踪仪位置优化

doi:10.3969/j.issn.1004-132X.2025.07.020

摘要/Abstract

摘要： 为解决激光跟踪仪在引导装配或下架检验中的位置优化问题，在数字孪生环境下提出一种基于Q学习的改进粒子群算法。首先建立激光跟踪仪的空间位置约束模型及装配车间要素仿真的数字孪生场景；然后构建马尔可夫决策模型来动态调整目标权重；最后以激光跟踪仪所在位置的通视率为评价基准，基于数字孪生环境进行验证并与其他算法进行性能对比。结果表明该算法在优化激光跟踪仪位置及通视率方面具有更好的效果。

关键词: 数字孪生, 激光跟踪仪, 飞机装配, 强化学习, 粒子群算法

Abstract: In order to solve the position optimization problems of laser trackers in guided assembly or off-shelf inspection, a Q-learning-based improved particle swarm optimization under digital twin environments was proposed herein. Firstly, a spatial position constraint model of the laser trackers and the digital twin scenario of the assembly shop element simulation were established. Secondly, a Markov decision model was constructed to dynamically adjust the target weight parameters. Finally, using pass-through rate of the laser tracker locations as evaluation benchmark, the algorithm was validated based on the digital twin environment and compared with other algorithms, which show that the algorithm has a better effectsiveness in optimizing the laser tracker locations and pass-through rate.

Key words: digital twin, laser tracker, aircraft assembly, reinforcement learning, particle swarm optimization

中图分类号:

文笑雨1, 张昊1, 张玉彦1, 刘思仁2, 吉硕1, 郭伟飞1, 李浩1. 数字孪生环境下飞机装配过程中的激光跟踪仪位置优化[J]. 中国机械工程, 2025, 36(07): 1573-1581,1635.

WEN Xiaoyu1, ZHANG Hao1, ZHANG Yuyan1, LIU Siren2, JI Shuo1, GUO Weifei1, LI Hao1. Optimization of Laser Tracker Positions in Aircraft Assembly Processes under Digital Twin Environments[J]. China Mechanical Engineering, 2025, 36(07): 1573-1581,1635.

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链接本文: https://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2025.07.020

https://www.cmemo.org.cn/CN/Y2025/V36/I07/1573

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