Autonomous Monitoring and Decision-Making System for Bridge Infrastructure

在过去的二十年中，传感器以前所未有的速度增长和采用，用于监测民用基础设施的性能和健康状况。这一增长主要是由以下因素综合造成的：意外的高调失败（例如，2007年I-35 W密西西比河大桥），需要延长老化基础设施的使用寿命，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，全球数十个结构都装有传感器，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。通过拟议的研究计划，我们的目标是弥合通过传感器获得的测量值和这些测量值的解释之间的差距，以产生有关结构健康的关键信息，特别是桥梁基础设施，通过理论，计算和算法工具的发展。这将使强大的技术交付到最终用户手中，而不需要用户拥有先进的技术专门知识，以有效地使用它。

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.