知识驱动的加工产品数字孪生拟态建模方法

对加工过程的实时观察、分析和控制是优化零部件加工策略的重要组成部分。通过融合几何状态、物理状态和设备状态变化等多维、实时的加工过程数据，可以实现对加工过程的建模和监控。数字孪生模型是数字孪生系统的核心与基础。但是，目前还缺乏一种系统且能自适应开发高保真、多尺度、多维加工数字孪生建模方法，以辅助系统进行分析与决策。提出了一种知识驱动的加工产品数字孪生拟态建模方法，可以在加工过程中自适应地构建产品数字孪生模型。该模型可根据加工过程自适应的变化，实时表达加工过程中的产品，为数字孪生决策系统提供数据支持。最后在一个航天零件的加工过程中测试了该方法，验证数字孪生拟态模型在加工中应用的可行性。

A Knowledge-Driven Digital Twin Modeling Method for Machining Products Based on Biomimicry

Real-time observation, analysis, and control of the machining process are the critical parts of optimizing the machining strategy of parts. By fusing multi-dimensional and real-time processing data such as geometry, physical state and equipment state, the modeling and monitoring of the machining process can be realized. The digital twin model is the core and foundation of the digital twin system. However, there is still a lack of a systematic and adaptive development modeling method of high-fidelity, multi-scale, multi-dimensional digital twin model. A knowledge-driven digital twin mimic modeling method for machining products is proposed, which can adaptively construct the digital twin model during the machining process. According to the adaptive evolution of the machining process, the model can express the products in the process in real-time and provide data support for the digital twin decision-making system. Finally, the method is tested in a case on an aerospace part to verify the feasibility of applying the digital twin mimic model in machining.