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Title:Development of a Long-term, Multimetric Structural Health Monitoring System for a Historic Steel Truss Swing Bridge
Author(s):Giles, Ryan K.; Spencer, Billie F., Jr.
Subject(s):structural health monitoring
steel truss bridge
historic bridge
fiber optic sensors
wireless sensors
first order flexibility method
statistical process control
Abstract: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.
Issue Date:2015-06
Publisher:Newmark Structural Engineering Laboratory. University of Illinois at Urbana-Champaign.
Series/Report:Newmark Structural Engineering Laboratory Report Series 039
Genre:Technical Report
Sponsor:Financial support for this research was provided in part by the Army Corps of Engineers Construction Engineering Research Laboratory (CERL) through a subcontract with Mandaree Enterprise Corporation.
Rights Information:Copyright held by the authors. All rights reserved.
Date Available in IDEALS:2015-06-18

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