Abstract: The assembly accuracy of large solid rocket engines and other complex products is difficult to be predicted under the action of multi-source error coupling.The concept of the digital twin was introduced to reveal the assembly error transmission mechanism of a manufacturing error,assembly deformation,and positioning error coupling.On this basis,a multi-dimensional and high-fidelity digital twin model construction and its driving method for assembly accuracy online analysis of complex assembly processes were proposed.A digital twin framework for online analysis of assembly accuracy was proposed from the perspective of coupling manufacturing error and assembly deformation.The complex assembly process data perception model,point cloud geometry model and assembly deformation mechanism model construction and fusion method were studied to form the complex assembly process multi-dimensional high-fidelity digital precision of online analysis and prediction.On this basis,with assembly features as nodes,based on the jacobian matrix and the model of the non-ideal surface,the complicated assembly process through access to the assembly site data assembly platform was realized.The intelligent large-scale solid rocket motor nozzle twin model was taken as the object to verify the correctness and effectiveness of the proposed technique,method and model.

Key words: assembly accuracy prediction, digital twin, manufacturing error, deformation error, positioning error

摘要： 针对多维误差耦合作用下大型固体火箭发动机等复杂产品装配过程中装配精度难以预测的问题,引入数字孪生概念,揭示制造误差、装配变形与定位误差耦合的装配偏差传递机理,据此提出一种复杂装配过程多维度高保真数字孪生模型构建及其驱动的装配精度在线分析方法。首先,从制造误差和装配变形耦合的角度,提出面向装配精度在线分析的数字孪生框架。其次,研究复杂装配过程数据感知模型、点云几何模型和装配变形机理模型的构建与融合方法,形成复杂装配过程多维度高保真数字孪生模型。在此基础上以装配特征为节点,基于雅可比矩阵和非理想表面模型,通过接入装配现场数据实现复杂装配过程装配精度在线分析与预测。最后,以大型固体火箭发动机喷管智能装配平台为对象,验证所提技术、方法与模型的正确性和有效性。

关键词: 装配精度预测, 数字孪生, 制造误差, 变形误差, 定位误差