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Long Term Monitoring of Millau Viaduct

机译:Millau高架桥的长期监控

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Millau Viaduct is a multi-span bridge located in the south of France which holds several world records: including longest cable stayed-bridge (2460 m) and tallest pier (245m). For megastructure like Millau Viaduct, performance monitoring is mandatory to guarantee the safety of users and optimize maintenance costs. Practically speaking, this is achieved through the continuous monitoring and the estimation of damage sensitive features extracted from static and dynamic measurements. This paper focuses on data analysis strategies carried out to extract these damage sensitive features. Regarding static measurements, operational and environmental effects are removed using iterative multilinear-regressions to reveal long term variations. The proposed approach is able to detect very light changes in piers tilt or in expansion joint movement. When dealing with dynamic measurements, natural frequencies are automatically identified through the method of frequency domain decomposition. The goal is to quantify their sensitivity to structural changes over a monitoring period of ten years. The study shows that once temperature effect is removed using regression methods, decrease of transversal frequencies is revealed which might be compatible with piers creeping.
机译:Millau高架桥是一座位于法国南部的多跨桥,拥有多项世界纪录:包括最长的斜拉桥(2460 m)和最高的桥墩(245m)。对于Millau高架桥等大型建筑,必须进行性能监控,以确保用户安全并优化维护成本。实际上,这是通过连续监视和估计从静态和动态测量中提取的损伤敏感特征来实现的。本文着重于为提取这些损伤敏感特征而进行的数据分析策略。关于静态测量,使用迭代多线性回归来消除长期变化,从而消除了操作和环境影响。所提出的方法能够检测到码头倾斜或伸缩缝运动中非常轻微的变化。在进行动态测量时,通过频域分解方法自动识别固有频率。目标是在十年的监视期内量化其对结构变化的敏感性。研究表明,一旦使用回归方法消除了温度影响,就会发现横向频率降低,这可能与桥墩蠕变兼容。

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