New method for modal identification of super high‐rise building structures using discretized synchrosqueezed wavelet and Hilbert transforms
New method for modal identification of super high‐rise building structures using discretized synchrosqueezed wavelet and Hilbert transforms
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DOI：
10.1002/tal.1312
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发表时间：
2017-02
期刊：
影响因子：
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通讯作者：
Zhijun Li;H. Park;H. Adeli
中科院分区：
文献类型：
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作者：
Zhijun Li;H. Park;H. Adeli
传感器在地震、风和波浪等动态事件期间获得的测量信号包含非线性、非平稳和噪声特性。本文提出了一种基于离散同步压缩小波变换、希尔伯特变换和线性最小二乘拟合相结合的结构模态参数识别新方法，特别适用于超高层建筑结构等大型现实结构。其有效性首先通过应用于文献中的二维框架得到证明，然后应用于韩国首尔正在建设的 123 层乐天世界大厦 (LWT)。 LWT 测量是非常低振幅的环境振动。众所周知，从此类低幅度信号中提取固有频率和阻尼比非常具有挑战性。此外，将新方法与经验模态分解进行了比较。事实证明，与经验模态分解方法相比，新方法能够有效地从低幅度信号中提取固有频率和阻尼比，并且具有更高的精度。这项研究的结果表明，像 LWT 这样的超高层建筑的阻尼比在 0.7-3.4% 范围内。这种新方法对于大型现实结构的健康监测的实际实施非常有前景。
Measured signals obtained by sensors during dynamic events such as earthquake, wind, and wave contain nonlinear, nonstationary, and noisy properties. In this paper, a new approach is presented for modal parameter identification of structures particularly suitable for very large real‐life structures such as super high‐rise building structures based on the integration of discretized synchrosqueezed wavelet transform, the Hilbert transform, and the linear least‐square fit. Its effectiveness is demonstrated first by application to a two‐dimensional frames from the literature, and then to the 123‐story Lotte World Tower (LWT) under construction in Seoul, Korea. The LWT measurements are very low‐amplitude ambient vibrations. Extracting the natural frequencies and damping ratios from such low‐amplitude signals are known to be very challenging. Further, the new methodology was compared with the empirical mode decomposition. It is demonstrated that the new method is capable of extracting both natural frequencies and damping rations from low‐amplitude signals effectively and with a higher accuracy compared with the empirical mode decomposition approach. The results of this research indicate a super high‐rise building like LWT has a damping ratio in the range 0.7–3.4%. The new method is quite promising for practical implementations of health monitoring of large real‐life structures.