机理与数据融合驱动的复杂航空复材部件关键装配误差元素辨识方法

doi:10.3969/j.issn.1004-132X.2025.07.016

摘要/Abstract

摘要： 复杂航空复材产品的装配中，考虑零件受力变形、多装配参数等因素，建立定位装夹、连接、下架回弹等关键装配环节的变形误差源模型，修正表示误差传递关系的雅可比旋量矩阵，构建装配误差传递机理模型；建立以装配误差为基础的支持向量回归模型，构建机理模型与数据模型的融合模型；依据装配误差机理模型计算值与实际偏差的预测补偿模型，采用Sobol灵敏度分析方法计算不同误差元素的全局灵敏度系数，辨识了对装配精度影响较大的关键误差元素。最后，以某机翼盒段装配为例验证了所提方法的有效性。

关键词: 机理模型, 数据驱动, 灵敏度分析, 机理数据融合建模, 复材装配

Abstract: In composite assembly of complex aviation products, the factors such as part deformations under loads, numerous parameters and so on were considered. Deformation error source models for key assembly links caused by positioning and clamping, joining and rebounding were analyzed, and the Jacobian sensor matrix representing error transmission relationship was modified to establish assembly error transmission mechanism model. A support vector regression model was established based on assembly error data, a fusion model of mechanism model and data model was gained. With the predication and compensation model for the calculated values of the error mechanism model and the actual deviation, a Sobol sensitivity analysis method was adopted to calculate the global sensitivity coefficients of different assembly error links, and the key error elements affecting assembly accuracy was identified. Finally, the assembly of wing box component was taken as an example to prove the effectiveness of the proposed method.

Key words: mechanism model, data driven, sensitivity analysis, mechanism-data fusion modeling, composite assembly

中图分类号:

V262

郭飞燕1, 张辉2, 宋长杰1, 张硕1. 机理与数据融合驱动的复杂航空复材部件关键装配误差元素辨识方法[J]. 中国机械工程, 2025, 36(07): 1530-1543.

GUO Feiyan1, ZHANG Hui2, SONG Changjie1, ZHANG Shuo1. Identification and Evaluation of Key Error Elements in Complex Composite Aviation Componts Assembly Driven by Mechanism and Data Model Fusion[J]. China Mechanical Engineering, 2025, 36(07): 1530-1543.

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链接本文: https://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2025.07.016

https://www.cmemo.org.cn/CN/Y2025/V36/I07/1530

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