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首页> 外文期刊>International journal of structural stability and dynamics >Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method
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Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method

机译：贝叶斯方法对长跨度斜拉桥（Sutong Bridge）的动态性质评价

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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.
机译：模态识别旨在识别包括固有频率，阻尼比和模式形状的动态特性，这是进一步结构损伤检测，有限元模型更新和条件评估的重要步骤。本文通过贝叶斯模态识别方法介绍了对长跨度斜拉桥桥梁桥梁动态特性的研究。 Sutong Bridge是世界上第二座最长的斜拉桥，位于中国江苏省的长江，总长度为2 088米。进行短期非破坏性的现场振动试验，以收集结构响应，并在其开放到交通之前确定桥的实际动态特性。由于传感器数量有限，设计了多种设置以完成整个测量。基于现场测试中收集的数据，通过快速贝叶斯FFT方法识别模态参数。识别和研究垂直和横向的前三种模式。为了获得温度和振动水平的模态参数变化，也在不同的季节中进行了长期测试。研究了具有温度和振动水平的固有频率和阻尼比的变化。还使用这些数据预先预测模态参数的未来分布。

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