New development on the modeling approaches is generally required to fusing the sensor data to the computational model in order to build up digital twins for the manufacturing processes. In this paper, we propose a modeling approach for building a digital twin for friction stir welding (FSW) based on a sensor-based numerical simulation. In the proposed approach, a novel iterative cyber-physics fusion algorithm is proposed to calculate the in-process 3D temperature field during FSW by fusing the measured temperature data to a ‘moving heat source’ analysis. Two FSW cases of commercial aluminum alloys AA2024 and AA6061 are analyzed to test the proposed modeling approach. It is demonstrated that the real-time calculating of the in-process 3D temperature field during FSW is highly feasible. When a timestep of 2.0 s is adopted, the proposed approach shows good reliability, as the average error between the measured and the calculated temperatures is less than 4 °C. More importantly, it is found that the calculation time for the whole welding process is shown to be less than the physical welding time. This allows that the sensor-based numerical simulation and the physical FSW process can be synchronized with a second-level temporal precision, which provides a viable cyber-physics fusion approach for digital twin modeling for the FSW process.

为了将传感器数据融合到计算模型中，通常需要对建模方法进行新的开发，以便为制造过程建立数字孪生模型。在本文中，我们提出了一种基于基于传感器的数值模拟来构建用于搅拌摩擦焊（FSW）的数字孪晶的建模方法。在提出的方法中，提出了一种新颖的电子物理物理迭代算法，通过将测得的温度数据融合到“移动热源”分析中来计算FSW期间的过程中3D温度场。分析了商用铝合金AA2024和AA6061的两个FSW案例，以测试所提出的建模方法。结果表明，FSW过程中实时3D温度场的实时计算是非常可行的。当采用2.0 s的时间步长时，由于所测温度与计算温度之间的平均误差小于4°C，因此所提出的方法显示出良好的可靠性。更重要的是，发现整个焊接过程的计算时间小于物理焊接时间。这使得基于传感器的数值模拟和物理FSW过程可以与第二级时间精度同步，从而为FSW过程的数字孪生建模提供了可行的电子物理融合方法。