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Statistical analysis of modal properties of a cable-stayed bridge through long-term structural health monitoring with wireless smart sensor networks

机译:通过无线智能传感器网络的长期结构健康监测,对斜拉桥的模态特性进行统计分析

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Understanding the dynamic behavior of complex structures such as long-span bridges requires dense deployment of sensors. Traditional wired sensor systems are generally expensive and time-consuming to install due to cabling. With wireless communication and on-board computation capabilities, wireless smart sensor networks have the advantages of being low cost, easy to deploy and maintain and therefore facilitate dense instrumentation for structural health monitoring. A long-term monitoring project was recently carried out for a cable-stayed bridge in South Korea with a dense array of 113 smart sensors, which feature the world's largest wireless smart sensor network for civil structural monitoring. This paper presents a comprehensive statistical analysis of the modal properties including natural frequencies, damping ratios and mode shapes of the monitored cable-stayed bridge. Data analyzed in this paper is composed of structural vibration signals monitored during a 12-month period under ambient excitations. The correlation between environmental temperature and the modal frequencies is also investigated. The results showed the long-term statistical structural behavior of the bridge, which serves as the basis for Bayesian statistical updating for the numerical model.
机译:要了解复杂结构(例如大跨度桥梁)的动态行为,需要密集部署传感器。传统的有线传感器系统由于布线而通常昂贵且安装耗时。凭借无线通信和机载计算功能,无线智能传感器网络具有成本低廉,易于部署和维护的优点,因此便于用于结构健康监控的密集仪表。最近,在韩国的斜拉桥上进行了一项长期监视项目,该桥具有113个智能传感器的密集阵列,这些传感器具有世界上最大的用于民用结构监视的无线智能传感器网络。本文对模态特性进行了全面的统计分析,包括所监测的斜拉桥的固有频率,阻尼比和模态。本文分析的数据由在环境激励下12个月内监测的结构振动信号组成。还研究了环境温度与模态频率之间的相关性。结果显示了桥梁的长期统计结构行为,为数值模型的贝叶斯统计更新奠定了基础。

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