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Visualization of Damage Detection for Circular Arch Based on Stochastic Subspace Identification

机译:基于随机子空间识别的圆拱损伤检测可视化

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When performing vibration tests on civil engineering structures, it is often unpractical and expensive to use artificial excitation (shakers, drop weights). Ambient excitation on the contrary is freely available (traffic, wind), but it causes other challenges. The ambient input remains unknown and the system identification algorithms have to deal with output-only measurements. The empirical mode decomposition (EMD) based stochastic subspace identification procedure utilizing operational vibration measurements is presented in this paper. The SSI method is then applied to the decomposed signals to yield the modal parameters of the hinged circular arch which is divided into sixteen elements, and then the strain mode shapes are obtained. In order to let the non-specialist to understand the message of the damages, the strain modes of the arch are presented with visual images. Visualization of damage detection has great potential for development of On-line structure health monitoring.
机译:在土木工程结构上进行振动测试时,使用人工激励(振动器,重锤)通常不切实际且昂贵。相反,环境激励是可自由获得的(交通,风),但它还会带来其他挑战。环境输入仍然未知,系统识别算法必须处理仅输出的测量。本文提出了基于经验模态分解(EMD)的基于随机子空间识别的操作振动测量方法。然后将SSI方法应用于分解后的信号,以产生铰链圆拱的模态参数,该参数被分为16个元素,然后获得应变模式形状。为了让非专业人士了解损坏的信息,在拱的应变模式下提供了可视图像。损伤检测的可视化对于开发在线结构健康监测具有巨大的潜力。

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