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Development of a Low-Cost Automated Tension Estimation System for Cable-Stayed Bridges

[+] Author Affiliations
Soojin Cho, Chung-Bang Yun

KAIST, Daejeon, South Korea

Jerome Peter Lynch

University of Michigan, Ann Arbor, MI

Paper No. SMASIS2008-614, pp. 279-287; 9 pages
doi:10.1115/SMASIS2008-614
From:
  • ASME 2008 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Smart Materials, Adaptive Structures and Intelligent Systems, Volume 2
  • Ellicott City, Maryland, USA, October 28–30, 2008
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-4332-1 | eISBN: 978-0-7918-3839-6
  • Copyright © 2008 by ASME

abstract

Cable tension force is one of the most important structural parameters to monitor in cable-stayed bridges. For example, cable tension needs to be monitored during construction and maintenance to ensure the bridge is not overloaded. To economically monitor tension forces, this study proposes the use of an automated wireless tension force estimation system (WFTES) developed solely for cable force estimation. The design of the WFTES system can be divided into two parts: low-cost hardware and automated software. The low-cost hardware consists of an integrated platform containing a wireless sensing unit constructed from commercial off-the-shelf components, a low-cost commercial MEMS accelerometer, and a signal conditioning board for signal amplification and filtering. With respect to the automated software, a vibration-based algorithm using estimated modal parameters and information on the cable sag and bending stiffness is embedded into the wireless sensing unit. Since modal parameters are inputs to the algorithm, additional algorithms are necessary to extract modal features from measured cable accelerations. To validate the proposed WFTES, a scaled-down cable model was constructed in the laboratory using steel rope wire. The wire was exposed to broad-band excitations while the WFTES recorded the cable response and embedded algorithms interrogated the measured acceleration to estimate tension force. The results reveal the embedded algorithms properly identify the lower natural frequencies of the cable and make accurate estimates of cable tension. This paper concludes with a summary of the salient research findings and suggestions for future work.

Copyright © 2008 by ASME

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