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Modal identification of Canton Tower under uncertain environmental conditions

机译:不确定环境条件下广州塔的模态识别

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摘要

The instrumented Canton Tower is a 610 m high-rise structure, which has been considered as a benchmark problem for structural health monitoring (SHM) research. In this paper, an improved automatic modal identification method is presented based on a natural excitation technique in conjunction with the eigensystem realization algorithm (NExT/ERA). In the proposed modal identification method, damping ratio, consistent mode indicator from observability matrices (CMI_O) and modal amplitude coherence (MAC) are used as criteria to distinguish the physically true modes from spurious modes. Enhanced frequency domain decomposition (EFDD), the data-driven stochastic subspace identification method (SSI-DATA) and the proposed method are respectively applied to extract the modal parameters of the Canton Tower under different environmental conditions. Results of modal parameter identification based on output-only measurements are presented and discussed. User-selected parameters used in those methods are suggested and discussed. Furthermore, the effect of environmental conditions on the dynamic characteristics of Canton tower is investigated.
机译:装有仪器的广州塔是610 m的高层结构,已被视为结构健康监测(SHM)研究的基准问题。本文提出了一种改进的基于自然激励技术的自动模态识别方法,并结合了本征系统实现算法(NExT / ERA)。在所提出的模态识别方法中,阻尼比,来自可观察性矩阵的一致模式指示符(CMI_O)和模态幅度相干性(MAC)被用作区分物理真实模式和伪模式的准则。分别采用增强频域分解(EFDD),数据驱动的随机子空间识别方法(SSI-DATA)和所提出的方法来提取不同环境条件下广州塔的模态参数。提出并讨论了基于仅输出测量值的模态参数识别结果。建议并讨论了这些方法中用户选择的参数。此外,研究了环境条件对广州塔动态特性的影响。

著录项

  • 来源
    《Smart structures and systems》 |2012年第5期|353-373|共21页
  • 作者单位

    School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China;

    School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China,State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510640, China;

    School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China;

    School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    high-rise structure; modal identification; ambient excitation; environmental condition;

    机译:高层建筑模式识别环境激发环境条件;

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