Infrared Imaging for Quantitative Defect Detection in Composite Structures

用于复合结构中定量缺陷检测的红外成像

• 批准号: 1362144
• 负责人: Francesco Lanza di Scalea
• 金额: $ 30万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1362144&HistoricalAwards=false
• 关键词: Infrared; Imaging; Quantitative; Defect; Detection

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.

由于其上级机械性能、重量轻和耐腐蚀性，复合材料被用于民用和军用部门的各种结构部件。由复合材料制成的部件在现代飞机中被发现（例如，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。不幸的是，由制造或操作条件引起的这些材料中的缺陷会大大降低结构的最终性能，甚至在灾难性故障的情况下影响人类安全。为了保证结构的性能和安全性，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体内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的缺陷检测提供了独特的优势，包括覆盖范围广，检测速度快和易于解释的诊断图像。该项目将通过改进复合材料中缺陷的尺寸和位置的确定来推进红外热成像的最新技术。这种能力将允许维护工程师和结构的业主在损伤检测事件后做出明智的补救措施决策，最终提高结构的可靠性和安全性。本项目的研究目标是通过实现定量缺陷检测来推进用于复合材料结构无损检测（NDT）的红外热成像技术。目前的热成像功能允许定性缺陷检测，定量预测仅基于简单和不切实际的1-D热扩散模型。本研究将开发一种基于“虚拟热源”（VHS）的新概念的复合材料的真实三维热扩散模型，以模拟由结构中的内部缺陷在主动加热后产生的多余表面热量。一个绿色的功能解决方案的3-D热扩散问题也将寻求占最一般的缺陷情况下（如非平面缺陷）。这些模型将预测测试对象中的温度场作为可量化缺陷特征的函数，包括（1）缺陷深度，（2）缺陷尺寸和（3）缺陷方向。理论模型将通过对UCSD现有样本进行的一系列实验性热成像测试进行验证和迭代，这些样本包括一个独特的9米长复合材料风力涡轮机叶片（CX-100叶片），其中包含45个记录良好的缺陷，以及几个代表复合材料飞机结构的面板。