Autonomous Monitoring and Decision-Making System for Bridge Infrastructure

在过去二十年中，用于监测民用基础设施的性能和健康状况的传感器出现了前所未有的增长和采用。这一增长主要是由多种因素共同造成的：意外的重大故障（例如，2013年卡尔加里CP铁路大桥，2007年I-35W密西西比河大桥），延长老化基础设施使用寿命的需要，以及相对低成本的测量和计算硬件的可用性。然而，这种增长在很大程度上是不平衡的，我们测量和存储数据的能力远远超过了我们从中提取有意义信息的能力。因此，全球许多结构都配备了传感器，而从数据中解释有用信息的关键任务仍然没有得到充分解决。通过提出的研究计划，我们的目标是通过发展理论、计算和算法工具，弥合通过传感器获得的测量结果与对这些测量结果的解释之间的差距，从而产生有关结构健康（特别是桥梁基础设施）的关键信息。这将使强大的技术交付到最终用户手中，而不需要用户为了有效地使用它而具有先进的技术专业知识。

There has been an unprecedented growth and adoption of sensors during the last two decades for the purpose of monitoring performance and health of civil infrastructure. This growth has resulted primarily from a combination of factors: unanticipated high-profile failures (e.g., 2013 CP Rail bridge in Calgary, 2007 I-35W Mississippi River bridge), the need to extend the service life of aging infrastructure, and an availability of relatively low-cost measurement and computing hardware. However, this growth has been largely lopsided, with our ability to measure and store data far surpassing our ability to extract meaningful information from them. As a result, scores of structures globally have been instrumented with sensors, while the key task of interpreting useful information from data remains inadequately addressed. Through the proposed research program, we aim to bridge the gap between measurements obtained through sensors and the interpretation of those measurements to produce crucial information regarding the health of structures, specifically bridge infrastructure, through the development of theoretical, computational, and algorithmic tools. This will enable the delivery of powerful technology into the hands of the end user, without the need for the user to have advanced expertise of the technology in order to use it effectively. To successfully bridge this gap, the following items must be adequately addressed: (i) development of an integrated framework bridging measurements with knowledge (knowledge management); (ii) autonomous implementation, where such information is extracted without the need for intervention of an expert user. Such a framework will allow users to respond if a structural component of a bridge has been compromised following a shock event (e.g., earthquake or vehicular impact), and it will enable users to estimate the remaining lifetime of the structure so that a proper intervention strategy, such as detailed inspection or replacement, can be planned. Through the development of autonomous algorithms, such information can be extracted with a limited need for an expert user. The proposal outlines a novel approach to integrate measurements with decision-making, made possible through a combination of theoretical, algorithmic and experimental developments. The proposed research program is transformative by trying to address the crucial gap between measurements and decision-making, thereby reducing the societal risk through the use of sensors. A successful implementation of this technology would enable us to not only save lives from catastrophic failures, but also allow us to extend the life of existing infrastructure, thereby saving capital costs. The inter-disciplinary training plan will train engineers who are equipped to use technology outside the traditional confines of civil engineering such as electronics and signal processing.