稀疏监测样本下的复合材料固化过程热源分布动态估计

Dynamic estimation of heat source distribution during solidification of composite materials under sparse monitoring samples

碳纤维增强树脂基复合材料(CFRP)具有优异的综合性能,已成为航空航天高端装备减重增效的优选材料。固化是实现复材构件成形承载的关键工艺环节,固化过程中的构件温度场直接决定了构件的成形质量与力学性能,如何精确、动态的反求复材构件表面的热源分布,是实现温度场精准调控的基础。然而实际的固化工艺需在构件表面贴附透气毡、真空袋等辅助材料,难以直接监测构件表面的温度场,仅能引入若干个光纤测温点获取稀疏的温度样本,给热源分布这一高维标量场的重构带来挑战。为此,提出一种基于高斯混合分布模型(GMM)的固化过程热源分布动态估计方法,引入高斯模糊与面内热扩散等效性这一物理先验,建立了基于高斯模糊的温度场演变模型,进而利用GMM中的多个高斯分布表征固化过程中的热源分布,将高维场重构难题转化为若干高斯分布参数的优化求解问题。通过仿真实验验证了本文方法的可行性与有效性,能够实现固化过程中热源分布的精确动态估计。

Carbon fiber reinforced polymer(CFRP)has excellent properties and has become the material of choice for reducing weight and enhancing efficiency in high-end aerospace equipment.Curing is a critical process in achieving the forming and load-bearing of a composite member.The temperature field of the component in the curing process directly determines the curing quality and mechanical properties of the component.Accurately and dynamically reversing the heat source distribution on the surface of the composite member is the key to realizing the accurate control of the temperature field.However,in the actual curing process,auxiliary materials such as breathable felt and vacuum bags are attached to the surface of the composite,making it difficult to directly monitor the surface temperature field.Only several optical fiber temperature measurement points can be introduced to obtain sparse temperature samples,posing challenges to the reconstruction of the high-dimensional scalar field of heat source distribution.Therefore,a dynamic estimation method of heat source distribution in the curing process based on Gaussian mixture distribution model(GMM)was proposed,which introduced the physical a priori equivalence of Gaussian fuzzy and in-plane heat diffusion,established a Gaussian fuzzy-based temperature field evolution model,and then use multiple Gaussian distributions in the GMM to characterize heat source distribution in the curing process,which transformed the difficult problem of high-dimensional field reconstruction into an optimization problem of solving several Gaussian distribution parameters.The feasibility and effectiveness of this method were verified by simulation experiments,demonstrating that it can achieve accurate dynamic estimation of heat source distribution during solidification.