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Development of a long-term, multimetric structural health monitoring system for a historic steel truss swing bridge.

机译：为一座历史悠久的钢桁架秋千桥开发了长期的，多指标的结构健康监测系统。

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摘要

The bridge stock across the United States is ageing, with many bridges approaching the end of their design life. The situation is so dire that the American Society of Civil Engineers gave the nation's bridges a grade of "C+" in the 2013 edition of their Report Card on America's Infrastructure. In fact, at the end of 2011, nearly a quarter of all bridges in the United States were classified as either structurally deficient or functionally obsolete. Thus, the nation's bridges are in desperate need of rehabilitation and maintenance. However, limited funds are available for the repair of bridges. Management of the nation's bridge infrastructure requires an efficient and effective use of available funds to direct the maintenance and repair efforts. Structural health monitoring has the potential to supplement the current routine of scheduled bridge inspections by providing an objective and detailed source of information about the status of the bridge.;This research develops a framework for the long-term monitoring of bridges that leverages multimetric data to provide value to the bridge manager. The framework is applied to the Rock Island Arsenal Government Bridge. This bridge is a historic, steel truss, swing bridge that spans the Mississippi River between Rock Island, IL and Davenport, IA. The bridge is owned and operated by the US Army Corps of Engineers (USACE) and is a vital link for vehicular, train, and barge traffic. The USACE had a system of fiber optic strain gages installed on the bridge. As part of this research, this system was supplemented with a wireless sensor network that measured accelerations on the bridge. The multimetric data from the sensor systems was collected using a program developed in the course of this research. The data was then analyzed and metrics were developed that could be used to determine the health of the structure and the sensor networks themselves. Statistical process control methods were established to detect anomalous behavior in the short and long term time scales. Methods to locate and quantify the damage that has occurred in the structure once an anomaly has been detected were demonstrated. One of the methods developed as part of this research was a first order flexibility method.;The SHM system this research develops has the desirable characteristics of being continuous temporally, multimetric, scalable, robust, autonomous, and informative. By necessity, some aspects of the developed SHM framework are unique and customized exclusively for the Rock Island Government Bridge. However, the principles developed in the framework are applicable to the development of an SHM system for any other bridge. Application of the SHM framework this research develops to other bridges has the potential to increase objectivity in the evaluation of bridges and focus maintenance efforts and funds on the bridges that are most critical to the public safety.
机译：美国各地的桥梁库存正在老化，许多桥梁的设计寿命已接近尾声。情况是如此的严峻，以至于美国土木工程师学会在其2013年版的《美国基础设施报告》中给美国桥梁定了“ C +”等级。实际上，在2011年底，美国所有桥梁中近四分之一被归类为结构缺陷或功能已过时。因此，国家的桥梁迫切需要修复和维护。但是，有限的资金可用于桥梁维修。国家桥梁基础设施的管理要求有效和有效地利用可用资金来指导维护和维修工作。通过提供客观，详细的有关桥梁状态的信息源，结构健康监测有可能补充当前计划的桥梁检查常规;本研究开发了一个长期监测桥梁的框架，该框架利用多度量数据来为桥梁经理提供价值。该框架适用于岩岛兵工厂政府大桥。这座桥是一座历史悠久的钢桁架旋转桥，横跨伊利诺伊州罗克岛和爱荷华州达文波特之间的密西西比河。这座桥由美国陆军工程兵团（USACE）拥有和运营，是车辆，火车和驳船交通的重要纽带。 USACE在桥上安装了一个光纤应变计系统。作为这项研究的一部分，该系统还配有无线传感器网络，该网络可测量桥梁上的加速度。使用本研究过程中开发的程序收集来自传感器系统的多度量数据。然后分析数据并开发度量，这些度量可用于确定结构和传感器网络本身的健康状况。建立了统计过程控制方法来检测短期和长期时间范围内的异常行为。一旦发现异常，就可以找到定位并量化在结构中发生的损坏的方法。作为本研究的一部分开发的方法之一是一阶灵活性方法。;本研究开发的SHM系统具有在时间上连续，多度量，可伸缩，健壮，自治且可提供信息的理想特征。必要时，已开发的SHM框架的某些方面是唯一的，并且是专门为岩岛政府大桥定制的。但是，该框架中开发的原理适用于任何其他桥梁的SHM系统的开发。这项研究开发的SHM框架在其他桥梁上的应用可能会增加评估桥梁的客观性，并将维护工作和资金集中在对公共安全最重要的桥梁上​​。

著录项

  • 作者

    Giles, Ryan Kent.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 363 p.
  • 总页数 363
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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