ERI: Drones-Enabled Active Sensing System (DEASS) for Detection of Subsurface Defects in Civil Infrastructure through Synchronized Drone Swarming and Thermal Imaging

ERI：无人机主动传感系统 (DEASS)，通过同步无人机群和热成像检测民用基础设施中的地下缺陷

• 批准号: 2139025
• 负责人: Johnny Li
• 金额: $ 19.99万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2139025&HistoricalAwards=false
• 关键词: ERI; Drones; Enabled; Active; Sensing

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This Engineering Research Initiation (ERI) project will explore an active thermal imaging system carried by a pair of drones, one (leader) for thermal imaging and the other (follower) for active heating (e.g., microwave), to enable subsurface defect detection in the next-generation inspection of civil infrastructure in a GPS-denied environment (e.g., underneath bridge decks). Due to its limited payload and battery time, a single drone cannot support additional payload and its associated accessories required for active sensing. The concept of two leader-follower drones is thus introduced. This award supports fundamental research for the development of a drones-enabled active sensing system through synchronized drone swarming and thermal imaging. The new technique will transform the current passive surface deterioration inspection practice, which is subject to the change in sunlight conditions, into an active thermal imaging inspection for subsurface condition deterioration, such as delamination and horizontal cracks in reinforced concrete structures. In addition to infrastructure inspection and maintenance, the new technique will impact multiple frontiers with cooperative robot swarming and active sensing, such as interactive manufacturing and healthcare, and academic communities in science and engineering. The technique and research results will be transferred into the hands of engineering professionals through a national workshop.The drones-enabled active sensing system will be investigated via software/hardware-in-the-loop simulations and experimental tests. This research will overcome two technical challenges: (1) to synchronize drone swarming and thermal imaging in an energy-efficient strategy and (2) to enable new thermal imaging detectability with a heat source distributed on a leader-follower drone platform to stimulate the appearance of subsurface defects in active imaging. It will lay a foundation on cooperative robot swarming and active sensing research in multiple frontiers. First, it will develop a new strategy of leader-follower formation for drone swarming with visual relative navigation and collision avoidance based on a three-dimensional stereo vision and potential field algorithm during cooperative active sensing and inspection of subsurface defects in a GPS-denied environment. Second, it will establish optimal characteristics of active sensing of microwave heated concrete decks with optimized microwave excitations (energy source, frequency and duration) and sensing protocols (measurement sensitivity, frame rate and time window). Third, it will develop a method to evaluate and improve the performance of cooperative drone swarm formation and active thermal imaging of defects in a markup solid deck concrete bridge and a potential field infrastructure inspection.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。这个工程研究启动(ERI)项目将探索一种由两架无人机携带的主动热成像系统，一架用于热成像，另一架(跟随者)用于主动加热(例如微波)，以在GPS拒绝的环境(例如桥面下)的下一代民用基础设施检查中实现地下缺陷检测。由于其有效载荷和电池时间有限，一架无人机无法支持主动传感所需的额外有效载荷及其相关附件。在此基础上提出了双主从无人机的概念。该奖项支持通过同步无人机群聚和热成像开发支持无人机的主动传感系统的基础研究。这项新技术将把目前受阳光条件变化影响的被动表面劣化检测方法转变为对钢筋混凝土结构分层和水平裂缝等地下条件劣化的主动热成像检测。除了基础设施的检查和维护，这项新技术还将通过协作的机器人集群和主动传感影响多个前沿，如交互式制造和医疗保健，以及科学和工程领域的学术界。技术和研究成果将通过一个全国性的工作室转移到工程专业人员手中。无人机启用的主动传感系统将通过软/硬件在环模拟和实验测试进行研究。这项研究将克服两个技术挑战：(1)以节能战略同步无人机集群和热成像；(2)利用分布在领先者-跟随者无人机平台上的热源实现新的热成像可探测性，以刺激主动成像中出现的亚表面缺陷。这将为多边界的协作机器人群体和主动感知研究奠定基础。首先，它将开发一种新的基于三维立体视觉和势场算法的无人机群领导-追随者编队策略，在GPS拒绝的环境中进行协作主动传感和地下缺陷检测。其次，它将建立优化的微波激励(能源、频率和持续时间)和传感方案(测量灵敏度、帧速率和时间窗口)的微波加热混凝土桥面主动传感的最佳特性。第三，它将开发一种方法来评估和改进合作无人机群的形成和对标记实体桥面混凝土桥梁中的缺陷的主动热成像以及潜在的现场基础设施检查的性能。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。