Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method

被引:29
|
作者
Ni, Yan-Chun [1 ]
Zhang, Qi-Wei [2 ]
Liu, Jian-Feng [1 ]
机构
[1] Tongji Univ, Dept Bridge Engn, Shanghai, Peoples R China
[2] Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Cable-stayed bridge; Sutong Bridge; field vibration test; Bayesian method; uncertainty quantification; AMBIENT MODAL IDENTIFICATION; FUNDAMENTAL 2-STAGE FORMULATION; FINITE-ELEMENT MODEL; FREE-VIBRATION DATA; SYSTEM-IDENTIFICATION; PART I; FREQUENCY-DOMAIN; IDENTIFIABILITY; POSTERIOR; DAMAGE;
D O I
10.1142/S0219455419400108
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Modal identification aims at identifying the dynamic properties including natural frequency, damping ratio, and mode shape, which is an important step in further structural damage detection, finite element model updating, and condition assessment. This paper presents the work on the investigation of the dynamic characteristics of a long-span cable-stayed bridge-Sutong Bridge by a Bayesian modal identification method. Sutong Bridge is the second longest cable-stayed bridge in the world, situated on the Yangtze River in Jiangsu Province, China, with a total length of 2 088 m. A short-term nondestructive on-site vibration test was conducted to collect the structural response and determine the actual dynamic characteristics of the bridge before it was opened to traffic. Due to the limited number of sensors, multiple setups were designed to complete the whole measurement. Based on the data collected in the field tests, modal parameters were identified by a fast Bayesian FFT method. The first three modes in both vertical and transverse directions were identified and studied. In order to obtain modal parameter variation with temperature and vibration levels, long-term tests have also been performed in different seasons. The variation of natural frequency and damping ratios with temperature and vibration level were investigated. The future distribution of the modal parameters was also predicted using these data.
引用
收藏
页数:22
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