Abstract
Structural Health Monitoring (SHM) technique has gained increasing attention in the areas of mechanical, aerospace and civil engineering over the past decades. Reliability analysis based on real-time SHM data can provide more timely and accurate assessment of present and future conditions of structures. Many researchers studied the reliability of bridges based on the field measurement data. However, most of the past researches focused on the reliability of certain component of bridges, such as the main cables. the suspenders. the stiffening girders and so on. Few literatures could be found on the reliability of entire bridge system. One of the obstacles is the correlation of stochastic responses of different components which is required for the computation of system reliability is usually missing. Simple assumptions of fully-correlated or uncorrelated cannot reflect the reality of bridges and may considerably compromise the accuracy of the analysis results. In light of this research need, this paper presents a correlation study of train-induced strain responses in a cable suspension bridge based on a comprehensive SHM system installed on the Tsing Ma Bridge in Hong Kong. Eight pairs of components, including four pairs of diagonal members and four pairs of bottom chords of longitudinal truss in two different sections were chosen in the correlation study. The correlations between peak strain responses of members in the same section, and members of different sections are discussed in details. Different correlation levels have been observed. The results of this study would shed light on the reliability analysis of the entire bridge system in future.
Original language | English |
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Title of host publication | [Missing Source Name from PIRA] |
Publisher | Department of Civil and Structural Engineering and Department of Mechanical Engineering, The Hong Kong Polytechnic University. |
ISBN (Print) | 9789623677318 |
Publication status | Published - Dec 2011 |
Keywords
- Correlation analysis
- Cable stayed bridge
- SHM
- Strain