Remote Infrastructure Monitoring Assessment via Multispectral Imaging of Surface Coatings

我国的基础设施老化和恶化，需要变革性的科学和技术，以协助新的管理和维护方法。该奖项支持监测，测量，分析和计算方面的基础研究，以支持适用于民用基础设施的系统诊断。例子包括桥梁、铁路、砖石建筑、管道网络、电力线、水坝等等。该奖项通过新型涂层研究多光谱成像，当沉积在实际结构部件上并由适当的成像设备监测时，这些涂层可作为选择性响应传感单元。该奖项的结果可用于实施前所未有的结构健康监测程序，该程序与为在高度动态环境中执行此类测量而开发的无人驾驶航空系统相结合，有可能从根本上减少与漫长而昂贵的维护操作相关的停机时间。此外，它们可以提供更早和更定量地识别劣化和损坏的能力。因此，这项研究的结果预计将有利于美国的经济和社会，因为它的目标是在制造，监测和分析方法与城市系统，基础设施的可持续性和弹性应用的重大改进。这项研究的更广泛影响集中在加强努力，在恢复和改善城市基础设施方面取得跨领域的进展。在公民参与的背景下，该研究将利用PI机构合作教育计划中的资源，在教育课程中转移相关知识，并培训下一代系统诊断领域的工程师。多模式遥感仪器平台与可扩展的制造和自主飞行器相结合，将创建一个框架，以快速评估基础设施系统的状况。该项目的三个研究目标是：在材料设计和超材料进步的背景下使用新型制造程序，为自动检测和变形量化的可扩展、可调、多模态、多光谱和嵌入式涂层创造前所未有的机会;使用配备有多光谱传感器的无人驾驶航空系统，能够通过询问涂层来测量变形;制定方法，将联合收割机多光谱图像点云以及其他信息源与多尺度和多模态建模相结合，以实现状态感知和剩余使用寿命预测。具体而言，将采用新的制造程序来设计表面涂层并将其嵌入结构部件中。涂层的特性将被定制，以确保通过捕获紫外线和红外线辐射以及可见光的多光谱传感器对其进行快速检测。涂层元件的相对位置将使用基于计算机视觉和摄影测量的专用算法进行跟踪，用于量化监测结构的局部和全局位置坐标。

Our country's aging and deteriorating infrastructure creates the need for transformative science and technology that can assist in novel management and maintenance approaches. This award supports fundamental research on monitoring, measurement, analysis and computations in support of system diagnostics, applicable to a civil infrastructure. Examples include bridges, railroads, masonry buildings, networks of pipelines, powerlines, dams and more. This award investigates multispectral imaging through novel coatings that act as selectively responsive sensing units when deposited on actual structural components and monitored by appropriate imaging devices. The results of this award could be used to implement unprecedented structural health monitoring procedures which combined with the use of unmanned aerial systems developed to perform such measurements in highly dynamic environments have the potential to radically reduce downtime associated with lengthy and costly maintenance operations. In addition, they may offer the capability of both earlier and more quantitative identification of deterioration and damage. Therefore, results of this research are expected to benefit the U.S economy and society as it targets major improvements in manufacturing, monitoring and analysis methods with applications in urban systems, sustainability and resiliency of infrastructure. The broader impact of this research focuses in enhancing the efforts for cross-cutting progress in restoration and improvement of urban infrastructure. In this context of civic engagement, the research will leverage resources within the PIs' institution co-operative educational program to transfer related knowledge in educational curricula and train the next generation of engineers working in the area of system diagnostics.Multimodal remote sensing instrumentation platform coupled with scalable manufacturing and autonomous aerial vehicles will create a framework to rapidly assess the condition of infrastructure systems. Three research objectives in this project are targeted: the use of novel manufacturing procedures in a context of a materials-by-design and advances in metamaterials for the creation of unprecedented opportunities for scalable, tunable, multimodal, multispectral and embedded coatings for automated inspection and deformation quantification; the use of unmanned aerial systems equipped with multi-spectral sensors capable to measure deformation through interrogation of the coatings; the development of methodologies to combine multispectral image point clouds, as well as other sources of information with multiscale and multimodal modeling for state awareness and remaining useful life predictions. Specifically, novel manufacturing procedures will be adopted to design surface coatings and embed them in structural components. The properties of the coatings will be tailored to guarantee their rapid detection by multispectral sensing capturing ultraviolet and infrared radiation as well as visible light. The relative position of the coating elements will be tracked using dedicated algorithms based on computer vision and photogrammetry used to quantify local and global position coordinates of the monitored structures.