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Title:Structural Health Monitoring for Bridge Structures using Smart Sensors
Author(s):Jang, Shin Ae; Spencer, Billie F., Jr.
Subject(s):Structural Health Monitoring
Wireless Smart Sensor Network
Decentralized Damage
Full-scale Bridge Monitoring
Abstract:Structural health monitoring (SHM) has drawn significant attention in recent decades because of its potential to reduce maintenance costs and increase the reliability of structures. An important class of structures that can potentially benefit from SHM are bridges, many of which are structurally deficient due to lack of adequate maintenance. Through condition assessment of these bridges, an effective plan of maintenance can be determined, offering the possibility to prolong service life, as well as to prevent catastrophic disasters due to sudden collapse. To date, numerous damage detection algorithms have been proposed. Still, challenges remain in applying such algorithms to monitor bridges in the field. In reality, the extent of an SHM system is limited by available budgets, which define the number of sensors that can be deployed. A solution to include many sensors within a limited budget with increased efficiency is to use a Wireless Smart Sensor Network (WSSN) because of the merits of low cost, easy installation, and effective data management. An acceleration-based SHM algorithm for WSSN has been developed with a decentralized network topology. This approach has been implemented into a modularized damage detection service. The SHM application is designed to leverage the on-board computation capability of the WSSN, reducing the transmitted data size by distributing the computation burden. The SHM application for WSSN has been validated in lab-scale experiments on a truss bridge model. Nonetheless, the real challenge of SHM is in the deployment on full-scale bridges for continuous monitoring. The usability and stability of WSSN has been validated on an architectural staircase in the Siebel Center. Based on the usability investigation, the deployment of the world’s largest WSSN on the Jindo Bridge, a cable-stayed bridge has been achieved in South Korea. The main purpose of the deployment was to validate the bridge monitoring system using WSSN and energy harvesting devices in a long-term manner. The ultimate goal of this report is to deploy the developed on-board decentralized damage identification application using WSSN on a historic truss bridge. As a first step, a series of dynamic tests were conducted for modal analysis using both wired and wireless sensor systems. During the tests, the functionality of the wireless sensor system with ISHMP Services Toolsuite was confirmed. For model-based damage identification approach developed herein, a finite element (FE) model was created. The initial FE model was updated based on a visual estimate of the corrosion. The updated model was used to generate baseline information for damage detection. Finally, the WSSN-based autonomous SHM system using the decentralized damage detection application was deployed on the historic bridge. The permanent SHM system was installed on the bridge, and the damage detection application was successfully run on the bridge. The damage detection results using the decentralized comprehensive application will be compared with those from the centralized approach using WSSN. The performance of WSSN and energy harvesting devices will be evaluated. In summary, this report provides a robust SHM system for bridge structures in use of WSSN.
Issue Date:2015-05
Publisher:Newmark Structural Engineering Laboratory. University of Illinois at Urbana-Champaign.
Series/Report:Newmark Structural Engineering Laboratory Report Series 035
Genre:Technical Report
Sponsor:Financial support for this research was provided in part by a Samsung Scholarship, the National Science Foundation (NSF) under NSF grant CMS 06-00433 (Dr. S. C. Liu, Program Manager), and the Global Research Network program from the Natural Research Foundation in Korea (NRF-2008-220-D00117).
Rights Information:Copyright held by the authors. All rights reserved.
Date Available in IDEALS:2015-06-18

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