Effect of multiple state characteristics on damage and wave propagation and compensation methods for damage detection

基于导波的结构健康监测系统必须能够检测和区分由结构损伤和外部环境条件等各种状态特征引起的导波传播变化，从而保证系统的可靠性。在第一个资助期，我们能够开发一个简单但强大的补偿温度对GUW传播的影响。除了实际测试场景中的温度外，外部静态载荷，例如由飞机机翼油箱中不同的燃油水平引起的负载，也决定了SHM系统必须在何种测试条件下运行。由于外载荷对热流传播的影响是可以测量的，因此会破坏现有的温度补偿方法。在这个子项目（SP）中，实验研究了温度和静载荷对GUW传播的同时影响，以开发同时补偿这两种状态特性的方法。此外，还将研究损伤对GUW传播的影响。为此，考虑了两种类型的纤维金属层压板（FML），即玻璃层压板铝增强环氧树脂（眩光）和碳纤维增强聚合物（CFRP）钢层压板，以映射阻抗和金属体积含量差异。为了有效地进行基于GUW的损伤诊断，建立有效的损伤分类（DC）是必不可少的前提。这些DC将与GUW信号相关联，从而能够进行全面诊断。由于冲击伤害占普通伤害的很大一部分，因此它是最重要的DC之一。冲击损伤特征包括基体开裂、金属与预浸料层间分层、纤维断裂、金属裂纹等。这些特征在不同的受影响样品中可能是相似的，这使得基于存在和不存在损伤特征的进一步区分分类变得困难。为了验证同一直流的样品是否可以进一步区分，在施加机械载荷后，通过x射线计算机断层扫描（CT）对其进行检查。假定这一过程使损伤模式的差异更加突出。特别是在冲击损伤的情况下，与新出现的损伤相比，已经不得不承受载荷，这些研究提供了进一步的子类，使发展的分类得以扩展。这些新的子类与GUW测量相关联，从而可以使用超声波监测扩大损伤诊断数据库。损伤特征将在SP3中用于模型验证，而根据dc标记的x射线CT和guw数据将在sp4中使用机器学习方法进行损伤诊断。由于还研究了机械载荷作用后传感器和电子元件的集成情况，因此研究结果为SP2中功能设计和集成方法的优化提供了基础。

A guided ultrasonic wave (GUW) based structural health monitoring (SHM) system must be able to detect and distinguish changes in GUW propagation resulting from various state characteristics, such as structural damage and external environmental conditions, to be reliable. In the first Funding Period we were able to develop a simple but powerful compensation for temperature influence on GUW propagation. In addition to the temperature in a realistic test scenario, external static loads, e.g. caused by different fuel levels in the tank of aircraft wings, also determine the test conditions under which a SHM system must operate. Since external loads have a measurable influence on the GUW propagation and thus could undermine the developed temperature compensation method. In this subproject (SP), the simultaneous influence of temperature and static load on GUW propagation is investigated experimentally in order to develop methods that compensate for both state characteristics simultaneously. The influence of damage on GUW propagation will also be investigated. For this purpose, two types of fibre-metal laminates (FML), namely Glass Laminate Aluminium Reinforced Epoxy (GLARE) and Carbon Fibre Reinforced Polymer (CFRP) steel laminates, are considered to map impedance and metal volume content differences. For efficient damage diagnostics based on GUW, establishing the validated damage classes (DC) is an essential prerequisite. These DC will be correlated with GUW signals and thus enable comprehensive diagnostics. Since impact damage makes up a large portion of common damage, it is one of the most important DC. Impact damage characteristics include matrix cracking, delamination between the metal and prepreg plies, fibre breakage, metal cracks etc. These characteristics can be similar in different affected samples, making further differential classification based on the presence and absence of damage characteristics difficult. In order to verify, whether samples of the same DC can be further differentiated, they are examined after the application of mechanical loads by means of X-ray computed tomography (CT). It is assumed that this procedure makes differences in the damage patterns more prominent. Especially in the case of impact damages which have already had to endure loads compared to newly emerged damage, these investigations provide further subclasses, enabling an extension of the developed taxonomy. These new subclasses are correlated with GUW measurements, which enables an enlarged database for damage diagnostics using ultrasonic monitoring. The damage characteristics will be used in SP3 for model validation while the X-ray CT and GUW-data labelled according to DCs are used in SP 4 for damage diagnosis with machine learning methods. Since the condition of integrated sensors and electronics after application of mechanical loads is also investigated, the results form the basis for optimizing the functional design and integration methods in SP2.