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 language | English |
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Title of host publication | Structural Health Monitoring 2013 |
Subtitle of host publication | A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013 |
Publisher | DEStech Publications |
Pages | 2736-2743 |
Number of pages | 8 |
Volume | 2 |
ISBN (Electronic) | 9781605951157 |
Publication status | Published - 1 Jan 2013 |
Event | 9th International Workshop on Structural Health Monitoring: A Roadmap to Intelligent Structures, IWSHM 2013 - Stanford University, Stanford, United States Duration: 10 Sept 2013 → 12 Sept 2013 |
Conference
Conference | 9th International Workshop on Structural Health Monitoring: A Roadmap to Intelligent Structures, IWSHM 2013 |
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Country/Territory | United States |
City | Stanford |
Period | 10/09/13 → 12/09/13 |
ASJC Scopus subject areas
- Computer Science Applications
- Health Information Management