Infrared Imaging for Quantitative Defect Detection in Composite Structures

复合材料因其优异的力学性能、轻质和耐腐蚀性能，被广泛应用于民用和军事领域的各种结构构件中。由复合材料制成的部件在现代飞机(如波音787和空中客车A380)、船舶、汽车、风力涡轮机、体育用品和许多其他高性能结构中都有应用。不幸的是，这些材料中的缺陷，无论是由制造条件还是操作条件引起的，都会极大地降低结构的最终性能，甚至在发生灾难性故障的情况下影响人类安全。为了保证结构性能和安全性，工程师需要知道缺陷的存在、大小和位置(就像肿瘤医生需要知道病人肿瘤的程度以最好地治愈它一样)。红外热成像技术为复合材料结构缺陷检测提供了独特的优势，包括覆盖面广、检测速度快和诊断图像易于理解。该项目将通过改进复合材料中缺陷的大小和位置的确定来推动红外热像技术的发展。这一能力将允许维护工程师和结构所有者在损伤检测事件发生后做出明智的补救步骤决定，最终提高结构的可靠性和安全性。该项目的研究目标是通过实现定量缺陷检测，推动红外热像技术用于复合材料结构的无损检测(NDT)。目前的热成像能力允许定性的缺陷检测，而定量预测仅基于简单和不切实际的一维热扩散模型。本研究将基于“虚拟热源”(VHS)的新概念，建立复合材料的真实三维热扩散模型，以模拟结构内部缺陷在主动加热后产生的过量表面热。还将寻求三维热扩散问题的格林函数解来解释最一般的缺陷情况(例如，非平面缺陷)。该模型将作为可量化缺陷特征的函数来预测测试对象中的温度场，这些缺陷特征包括(1)缺陷深度、(2)缺陷大小和(3)缺陷取向。理论模型将通过对加州大学圣迭戈分校现有试件进行的一系列实验热像测试来验证和迭代，其中包括一种独特的9米长的复合材料风力涡轮机叶片(CX-100叶片)，其中包含45个有详细记录的缺陷，以及几个代表复合材料飞机结构的面板。

Due to their superior mechanical performance, light-weight and resistance to corrosion, composite materials are used in a variety of structural components in the civil and military sectors. Parts made of composite materials are found in modern aircraft (e.g., Boeing 787 and Airbus A380), ships, cars, wind turbines, sporting goods and many other high performance structures. Unfortunately, defects in these materials, caused by either manufacturing or operational conditions, can greatly reduce the ultimate performance of the structure, and even impact human safety in the case of catastrophic failures. In order to guarantee structural performance and safety, engineers need to know the presence, size and position of the flaws (in much the same manner that an oncologist doctor needs to know the extent of a tumor in a patient to best cure it). The technique of Infrared Thermography offers unique advantages for defect detection in composite structures, including broad coverage, speed of inspection and easily-interpretable diagnostic images. This project will advance the state-of-the-art in Infrared Thermography by improving the determination of the size and the position of a flaw in the composite material. This capability will allow maintenance engineers and structures' owners to make informed decisions on remedial steps following a damage detection event, ultimately increasing the reliability and the safety of the structure.The research goal of this project is to advance the known technique of Infrared Thermography for the Non-Destructive Testing (NDT) of composite structures by enabling quantitative defect detection. Current Thermographic capabilities allow for qualitative defect detection, with quantitative predictions only based on simplistic and unrealistic 1-D heat diffusion models. This research will develop realistic 3-D heat diffusion models for composite materials based on a novel concept of "Virtual Heat Source" (VHS) to simulate the excess surface heat produced by an internal defect in the structure following active heating. A Green's function solution to the 3-D heat diffusion problem will be also sought to account for the most general defect cases (e.g. non-planar defects). The models will predict the temperature field in the test object as a function of quantifiable defect features, including (1) defect depth, (2) defect size, and (3) defect orientation. The theoretical models will be validated and iterated by a series of experimental thermographic tests conducted on existing specimens at UCSD, including a unique, 9-m long composite wind turbine blade (CX-100 blade) containing 45 well-documented defects, and several panels representative of composite aircraft construction.