结构健康监测
甲板
桥(图论)
工作模态分析
结构工程
工程类
悬挂(拓扑)
情态动词
振动
风力工程
跨度(工程)
模态分析
材料科学
有限元法
医学
物理
内科学
同伦
高分子化学
纯数学
量子力学
数学
作者
Ki Young Koo,James Brownjohn,David List,Richard Cole
摘要
This paper presents experiences and lessons from the structural health monitoring practice on the Tamar Bridge in Plymouth, UK, a 335-m span suspension bridge opened in 1961. After 40 years of operations, the bridge was strengthened and widened in 2001 to meet a European Union Directive to carry heavy goods vehicles up to 40 tonnes by a process in which additional stay cables and cantilever decks were added and the composite deck was replaced with a lightweight orthotropic steel deck. At that time, a structural monitoring system comprising wind, temperature, cable tension and deck level sensors was installed to monitor the bridge behaviour during and after the upgrading. In 2006 and 2009, respectively, a dynamic response monitoring system with real-time modal parameter identification and a robotic total station were added to provide a more complete picture of the bridge behaviour, and in 2006 a one-day ambient vibration survey of the bridge was carried out to characterize low-frequency vibration modes of the suspended structure. Practical aspects of the instrumentation, data processing and data management are discussed, and some key response observations are presented. The bridge is a surprisingly complex structure with a number of inter-linked load–response mechanisms evident, all of which have to be characterized as part of a long-term structural health monitoring exercise. Structural temperature leading to thermal expansion of the deck, main cables and additional stays is a major factor on global deformation, whereas vehicle loading and wind are usually secondary factors. Dynamic response levels and modal parameters show apparently complex relationships among themselves and with the quasi-static load and response. As well as the challenges of fusing and managing data from three distinct but parallel monitoring systems, there is a significant challenge in interpreting the load and response data firstly to diagnose the normal service behaviour and secondly to identify performance anomalies. Copyright © 2012 John Wiley & Sons, Ltd.
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