Autonomous Monitoring and Decision-Making System for Bridge Infrastructure

桥梁基础设施自主监测与决策系统

• 批准号: RGPIN-2017-03922
• 负责人: Narasimhan, Sriram
• 金额: $ 2.99万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=660649
• 关键词: Autonomous; Monitoring; Decision; Making; System

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.**

在过去的二十年中，传感器的增长和采用一直存在，目的是监测民用基础设施的绩效和健康。这种增长主要来自多种因素：意外的高调失败（例如，卡尔加里的2013年CP Rail桥，2007年I-35W密西西比河桥），需要延长基础设施老化的服务寿命，以及相对较低的测量和计算硬件的可用性。但是，这种增长在很大程度上被误导了，我们有能力测量和存储数据，超过了我们从中提取有意义信息的能力。结果，全球几个结构已使用传感器进行了仪器，而解释来自数据的有用信息的关键任务仍然不足。通过拟议的研究计划，我们旨在弥合通过传感器获得的测量和解释这些测量结果之间的差距，以通过开发理论，计算和算法工具的开发，从而产生有关结构健康，特别是桥梁基础设施的关键信息。这将使功能强大的技术能够交付到最终用户的手中，而无需用户拥有该技术的高级专业知识以有效地使用它。******为了成功弥合这一差距，必须充分解决以下项目：（i）开发集成的框架架起了具有知识管理（知识管理）的综合框架测量值； （ii）自主实现，在不需要专家用户干预的情况下提取此类信息。如果桥梁的结构成分在发生冲击事件（例如，地震或车辆撞击）后，这种框架将允许用户做出响应，并且可以计划估算结构的剩余寿命，以便可以计划进行适当的干预策略，例如可以计划进行详细的检查或更换。通过开发自主算法，可以提取此类信息，而对于专家用户的需求有限。 *****该提案概述了一种将测量与决策相结合的新方法，通过理论，算法和实验发展的结合，使其成为可能。提出的研究计划是通过试图解决测量和决策之间的关键差距，从而通过使用传感器来降低社会风险的转变性。这项技术的成功实施将使我们不仅能够从灾难性的失败中挽救生命，而且还使我们能够延长现有基础设施的寿命，从而节省了资本成本。跨学科培训计划将培训能够在土木工程和信号处理等土木工程范围之外使用技术的工程师。**