Online automatic identification of the modal parameters of a long span arch bridge
Online automatic identification of the modal parameters of a long span arch bridge
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DOI：
10.1016/j.ymssp.2008.05.003
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发表时间：
2009-02-01
影响因子：
8.4
通讯作者：
Caetano, Elsa
中科院分区：
文献类型：
--
作者：
Magalhaes, Filipe;Cunha, Alvaro;Caetano, Elsa
《D王子》恩里克大桥是一座混凝土拱桥，跨度为280米，横跨杜罗河，连接葡萄牙北部的波尔图和盖亚两座城市。最近安装的动态监测系统正在监测这一结构，该系统包括12个加速通道。本文介绍了桥梁结构，其动态参数确定与以前开发的环境振动测试，安装的监测设备和软件，不断处理收到的数据从桥梁通过互联网连接。特别强调的是，已经开发和实施的算法，以执行在线自动识别的结构模态参数从其测量的响应在正常运行期间。所提出的方法使用协方差驱动的随机子空间识别方法（SSI-COV），然后补充了一个新的算法开发的稳定图的自动分析。这种新的工具，基于层次聚类算法，被证明是非常有效的桥梁的前12个模式的识别。详细介绍了在2个月的观察期间取得的结果，其中涉及2500多个数据集的分析。它表明，与高品质的设备和强大的识别算法相结合，它是可能的，以自动的方式，精确的模态参数估计为几个模式。然后，这些可以用作损伤检测算法的输入。(C)2008爱思唯尔有限公司保留所有权利。
The "Infante D. Henrique" bridge is a concrete arch bridge, with a span of 280m that crosses the Douro River, linking the cities of Porto and Gaia located in the North of Portugal. This structure is being monitored by a recently installed dynamic monitoring system that comprises 12 acceleration channels. This paper describes the bridge structure, its dynamic parameters identified with a previously developed ambient vibration test, the installed monitoring equipment and the software that continuously processes the data received from the bridge through an Internet connection. Special emphasis is given to the algorithms that have been developed and implemented to perform the online automatic identification of the structure modal parameters from its measured responses during normal operation. The proposed methodology uses the covariance driven stochastic subspace identification method (SSI-COV), which is then complemented by a new algorithm developed for the automatic analysis of stabilization diagrams. This new tool, based on a hierarchical clustering algorithm, proved to be very efficient on the identification of the bridge first 12 modes. The results achieved during 2 months of observation, which involved the analysis of more than 2500 datasets, are presented in detail. It is demonstrated that with the combination of high-quality equipment and powerful identification algorithms, it is possible to estimate, in an automatic manner, accurate modal parameters for several modes. These can then be used as inputs for damage detection algorithms. (C) 2008 Elsevier Ltd. All rights reserved.