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Proceedings Paper

Long-term assessment of an autonomous wireless structural health monitoring system at the new Carquinez Suspension Bridge
Author(s): Masahiro Kurata; Junhee Kim; Yilan Zhang; Jerome P. Lynch; G. W. van der Linden; Vince Jacob; Ed Thometz; Pat Hipley; Li-Hong Sheng
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Paper Abstract

A dense network of sensors installed in a bridge can continuously generate response data from which the health and condition of the bridge can be analyzed. This approach to structural health monitoring the efforts associated with periodic bridge inspections and can provide timely insight to regions of the bridge suspected of degradation or damage. Nevertheless, the deployment of fine sensor grids on large-scale structures is not feasible using wired monitoring systems because of the rapidly increasing installation labor and costs required. Moreover, the enormous size of raw sensor data, if not translated into meaningful forms of information, can paralyze the bridge manager's decision making. This paper reports the development of a large-scale wireless structural monitoring system for long-span bridges; the system is entirely wireless which renders it low-cost and easy to install. Unlike central tethered data acquisition systems where data processing occurs in the central server, the distributed network of wireless sensors supports data processing. In-network data processing reduces raw data streams into actionable information of immediate value to the bridge manager. The proposed wireless monitoring system has been deployed on the New Carquinez Suspension Bridge in California. Current efforts on the bridge site include: 1) long-term assessment of a dense wireless sensor network; 2) implementation of a sustainable power management solution using solar power; 3) performance evaluation of an internet-enabled cyber-environment; 4) system identification of the bridge; and 5) the development of data mining tools. A hierarchical cyber-environment supports peer-to-peer communication between wireless sensors deployed on the bridge and allows for the connection between sensors and remote database systems via the internet. At the remote server, model calibration and damage detection analyses that employ a reduced-order finite element bridge model are implemented.

Paper Details

Date Published: 18 April 2011
PDF: 9 pages
Proc. SPIE 7983, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2011, 798312 (18 April 2011); doi: 10.1117/12.880145
Show Author Affiliations
Masahiro Kurata, Univ. of Michigan (United States)
Junhee Kim, Univ. of Michigan (United States)
Yilan Zhang, Univ. of Michigan (United States)
Jerome P. Lynch, Univ. of Michigan (United States)
G. W. van der Linden, SC Solutions, Inc. (United States)
Vince Jacob, SC Solutions, Inc. (United States)
Ed Thometz, California Dept. of Transportation (United States)
Pat Hipley, California Dept. of Transportation (United States)
Li-Hong Sheng, California Dept. of Transportation (United States)


Published in SPIE Proceedings Vol. 7983:
Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2011
H. Felix Wu, Editor(s)

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