Quantitative Defect Reconstruction in Active Thermography for Fiber-Reinforced Composites
Quantitative Defect Reconstruction in Active Thermography for Fiber-Reinforced Composites
复制标题
纤维增强复合材料主动热成像中的定量缺陷重建
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
M. Weiser
中科院分区：
文献类型：
--
作者：
Sebastian Götschel;C. Maierhofer;Jan P. Müller;N. Rothbart;M. Weiser
碳纤维增强复合材料在汽车和航空航天等轻质结构的生产中发挥着越来越重要的作用。热像仪通常用于这些产品的无损检测，特别是检测复合材料不同层之间的分层。在本报告中，我们的目标是根据碳纤维增强复合材料的热像测量来重建缺陷的方法。重建结果不仅应允许定位缺陷，而且还应给出缺陷的几何特性的定量表征。讨论了用有限元方法对测量过程进行模拟，并进行了实验验证。为了考虑纤维的各向异性热输运，我们比较了用单个扩散张量单独描述层和用平均扩散张量描述层的情况。特别是在脉冲热像仪中，需要解决加热表面温度梯度较大的薄边界层问题。在这里，我们考虑一维解析解和剩余缺陷方程的数值解的组合。此外，我们还讨论了分层和起伏等各种缺陷的数学模型，以及不均匀加热的几何光学描述。最后，我们将描述基于偏微分方程的反问题求解方法，以及避免昂贵计算的快速启发式方法的思想。
Carbon-fiber reinforced composites are becoming more and more important in the production of light-weight structures, e.g. in the automotive and aerospace industry. Thermography is often used for non-destructive testing of these products, especially to detect delaminations between different layers of the composite. In this presentation, we aim at methods for defect reconstruction from thermographic measurements of such carbon-fiber reinforced composites. The reconstruction results shall not only allow locating defects, but also give a quantitative characterization of the geometric properties of the defect. We discuss the simulation of the measurement process using finite element methods, as well as the experimental validation. In order to take anisotropic heat transport due to the fibers into account, we compare describing layers separately by individual diffusion tensors with using an averaged diffusion tensor. Especially in pulse thermography, thin boundary layers with steep temperature gradients occurring at the heated surface need to be resolved. Here we consider the combination of a 1D analytical solution combined with numerical solution of the remaining defect equation. Moreover, we discuss the mathematical modelling of various defects like delaminations and undulations, as well as the description of inhomogeneous heating by geometric optics. Finally, we will describe PDE-based methods for the solution of the inverse problem as well as ideas for fast heuristic methods to avoid expensive computations.