Control of flow in resin transfer molding with real‐time preform permeability estimation
Control of flow in resin transfer molding with real‐time preform permeability estimation
复制标题
通过实时预成型件渗透性估计来控制树脂传递模塑中的流动
DOI：
10.1002/pc.10504
复制
发表时间：
2002
影响因子：
5.2
通讯作者：
R. Pitchumani
中科院分区：
文献类型：
--
作者：
D. R. Nielsen;R. Pitchumani
在模具中原位的预成型件结构的可变性是在液体模制工艺中实现可靠的预成型件饱和的公认挑战。物理模型提供了一种有效的手段来获得实时过程控制决策，以便以所需的方式引导树脂流动，这确保了完全的预成型件饱和。影响模拟保真度的一个重要参数是预制件的渗透性，这是一个强大的功能的预制件的微观结构。一个基于模型的控制策略，结合了实时确定和利用当地渗透率信息的能力是非常有价值的，并形成了本文的重点。开发了一种基于模型的智能控制器，该控制器使用渗透率的虚拟传感来获得控制树脂传递模塑（RTM）过程中模具入口处的注射压力的最佳决策。该控制器采用人工神经网络，训练使用过程模拟数据，作为一个在线的流量模拟器，和模拟退火算法，以优化注射压力的过程中的飞行。基于流动前沿速度和沿流动前沿沿着的局部压力梯度，使用模糊逻辑模型估计，在该过程期间虚拟地感测预成型件渗透率。的控制器，实施RTM工艺，被证明是能够准确地引导通过各种预成型配置的流动前沿。
Variabilities in the preform structure in situ in the mold are an acknowledged challenge to achieving reliable preform saturation in liquid molding processes. Physical models offer an effective means of deriving real-time process control decisions so as to steer the resin flow in a desired manner, which ensures complete preform saturation. An important parameter influencing the fidelity of the simulations is the preform permeability, which is a strong function of the preform microstructure. A model-based control strategy that incorporates the ability to determine and utilize local permeability information in real-time is of much value, and forms the focus of the paper. An intelligent model-based controller is developed that uses virtual sensing of permeability to derive optimal decisions on controlling the injection pressures at the mold inlet ports in a resin transfer molding (RTM) process. The controller employs an artificial neural network, trained using process simulation data, as an on-line flow simulator, and a simulated annealing algorithm to optimize the injection pressures on-the-fly during the process. Preform permeability is virtually sensed during the process, based on the flow front velocities and the local pressure gradient along the flow front, estimated using a fuzzy logic model. The controller, implemented on an RTM process, is shown to be able to accurately steer the flow fronts through various preform configurations.