Structural Identification Using Computer Vision–Based Bridge Health Monitoring
Publication: Journal of Structural Engineering
Volume 144, Issue 2
Abstract
This paper presents a new structural identification (St-Id) framework along with a damage indicator, displacement unit influence surface using computer vision–based measurements for bridge health monitoring. Unit influence surface (UIS) of a certain response (e.g., displacement, strain) at a measurement location on a beam-type or plate-type structure (e.g., single-span or multispan bridge with its deck) is defined as a response function of the unit load with respect to the any given location of the unit load on that structure. The novel aspect of this paper is a framework integrating vehicle load (input) modeling using computer vision and the development of a new damage indicator, UIS, using image-based structural identification. This framework is demonstrated on the large-scale bridge model in the University of Central Florida Structures Laboratory for verification and validation. The UIS damage indicators successfully identified the simulated damage on the bridge model, including damage detection and damage localization.
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Acknowledgments
This work was supported by National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation (Grant No. 1463493); partially through a fellowship from the Scientific and Technological Research Council of Turkey (Türkiye Bilimsel ve Teknolojik Arastirma Kurumu—TUBITAK); and the West Nippon Expressway Co., Ltd. The authors would like to express their sincere gratitude for these agencies, responsible administrators, the graduate students in the Prof. Catbas’ research group.
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Information & Authors
Information
Published In
Journal of Structural Engineering
Volume 144 • Issue 2 • February 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jan 15, 2016
Accepted: Jun 30, 2017
Published online: Nov 28, 2017
Published in print: Feb 1, 2018
Discussion open until: Apr 28, 2018
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