Reliability-based condition assessment of bridge deck using long-term monitoring data

Yiqing Ni, K. C. Lin

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

1 Citation (Scopus)

Abstract

We propose a reliability-based approach for progressive assessment of structural condition of bridge deck sections, and apply the proposed method to the suspension Tsing Ma Bridge with the use of long-term strain monitoring data. After performing wavelet multi-resolution analysis to extract the live-load-caused strain components from raw measurement data, the strain sequences acquired from different structural members on the same deck section are synthesized to derive the dynamic internal forces (axial force, bending moment, and shear force) of the monitored deck section. The Weibull mixture modeling is then carried out to characterize the probability density distribution of the peaks of each internal force component, and the corresponding reliability index is obtained. The reliability index of the deck section is evaluated by considering the different internal force components in series connection. The evaluation result of reliability index at deck section level is obtained year by year with cumulated strain monitoring data, thus tracking the variation in structural condition of the bridge deck evolutionarily.
Original languageEnglish
Title of host publicationStructural Health Monitoring 2013
Subtitle of host publicationA Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013
PublisherDEStech Publications
Pages2736-2743
Number of pages8
Volume2
ISBN (Electronic)9781605951157
Publication statusPublished - 1 Jan 2013
Event9th International Workshop on Structural Health Monitoring: A Roadmap to Intelligent Structures, IWSHM 2013 - Stanford University, Stanford, United States
Duration: 10 Sept 201312 Sept 2013

Conference

Conference9th International Workshop on Structural Health Monitoring: A Roadmap to Intelligent Structures, IWSHM 2013
Country/TerritoryUnited States
CityStanford
Period10/09/1312/09/13

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Information Management

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