A SHM-oriented test-bed for long-span suspension bridges: Settlement study

You Lin Xu, X. H. Zhang, Songye Zhu, S. Zhan, Hwa Yaw Tam, H. Y. Au

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper presents both experimental and numerical studies to examine the effects of support settlement on structural response of a long-span suspension bridge and explore the possibility of using measured responses to detect the support settlement of the bridge. A laboratory-based test-bed, including a delicate physical model and a corresponding updated finite element model (FEM) of a long-span suspension bridge with various settlement scenarios implemented is first introduced. The instrumentation and experimental procedure is then described. Two cases of anchorage settlement and two cases of tower settlement were experimentally studied to find their effects on bridge responses. The experimental results are compared with those computed from the updated FEM. The agreement of the results demonstrates that the FEM is a good representation of the physical model and can serve as a structural health monitoring (SHM) benchmark of long-span suspension bridges. Based on the FEM, the relationship between the structural response and the support settlement is finally utilized to develop a method for detecting the support settlement of the bridge.
Original languageEnglish
Title of host publicationSHMII-5 2011 - 5th International Conference on Structural Health Monitoring of Intelligent Infrastructure
Publication statusPublished - 1 Dec 2011
Event5th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII-5 2011 - Cancun, Quintana Roo, Mexico
Duration: 11 Dec 201115 Dec 2011

Conference

Conference5th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII-5 2011
Country/TerritoryMexico
CityCancun, Quintana Roo
Period11/12/1115/12/11

ASJC Scopus subject areas

  • Artificial Intelligence
  • Civil and Structural Engineering
  • Building and Construction

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