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Bayesian operational modal analysis and assessment of a full-scale coupled structural system using the Bayes-Mode-ID method

机译:使用贝叶斯-ID-方法对全尺寸耦合结构系统进行贝叶斯操作模态分析和评估

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This paper presents a structural assessment project for a construction training center in Hong Kong. The training center consists of coupled main and complementary buildings. Due to the vigorous activities in the training center, the objectives of the project include conducting operational modal analysis (OMA) of the buildings to assess their structural performance and the coupling of vibrations between the two buildings. OMA is conducted using Bayes-Mode-ID recently developed by the authors, which is an efficient Bayesian modal-component-sampling system identification method for field testing of civil engineering structures under ambient vibrations. Implementation issues for Bayes-Mode-ID are discussed in detail for the full-scale coupled structural system. Due to the large number of measurement points (high resolution mode shapes are desired for understanding the coupling behavior of the system) and limited number of sensors, the measurements were divided into 21 setups in order to properly characterize the dynamics of the building. Each setup covered one portion of the training center and the partial mode shapes from different setups were assembled to provide the global mode shapes. By following a Bayesian approach, not only the most probable values (MPVs) of the modal parameters (modal frequencies, modal damping ratios and mode shapes) but also their associated uncertainties can be obtained. The identified modal parameters reveal interesting dynamic behaviors of the coupled-building and they will be helpful for structural assessment and structural health monitoring (SHM) of the training center in the future.
机译:本文介绍了香港建筑培训中心的结构评估项目。培训中心由主楼和互补楼组成。由于培训中心的积极活动,该项目的目标包括对建筑物进行运行模态分析(OMA),以评估其结构性能以及两座建筑物之间的振动耦合。 OMA使用作者最近开发的Bayes-Mode-ID进行,这是一种有效的Bayes模态分量采样系统识别方法,用于在环境振动下对土木工程结构进行现场测试。针对完整耦合结构系统,详细讨论了贝叶斯模式ID的实现问题。由于大量的测量点(需要高分辨率模式的形状才能理解系统的耦合性能)和传感器的数量有限,因此将测量结果分为21种设置,以正确表征建筑物的动态特性。每个设置覆盖了培训中心的一部分,并且组装了来自不同设置的部分模式形状以提供全局模式形状。通过遵循贝叶斯方法,不仅可以获得模态参数(模态频率,模态阻尼比和模态形状)的最可能值(MPV),而且可以获得其相关的不确定性。所识别的模态参数揭示了耦合建筑物的有趣动态行为,它们将有助于将来培训中心的结构评估和结构健康监测(SHM)。

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