【摘要】 提出了基于相关函数预估计和渐近小波分析的结构系统识别方法,此方法可以从结构随机环境振动响应中识别出结构的模态参数和物理参数。证明了在广谱白噪声环境激励下,结构随机振动相关响应的Morlet小波系数图的脊线值包含了解耦的结构模态信息,可用于结构的模态参数识别。如果知道随机激励的功率谱强度,还可以识别结构的质量、刚度和阻尼矩阵等物理参数。三层框架结构数值算例的结果表明上述方法可以准确地从结构随机振动响应信号中识别出结构参数。苏通大桥北索塔环境振动测试试验研究的结果表明此方法对于工程结构环境激振下的结构模态识别具有很好的效果。更多还原

【Abstract】 In this paper, a covariance-driven wavelet analysis technique is proposed for identifying the characteristics of linear structural systems from random vibration response measurements. Based on the asymptotic wavelet analysis theory, the paper proves that the ridges of Morlet wavelet coefficient magnitudes of structural covariance response under random excitations contain structural modal information and can be used to estimate structural modal parameters. In addition, if the spectral intensity of the random load is known, structural mass, stiffness and damping matrices can also be estimated. Results of a numerical study on a 3-storey frame show that the proposed technique can accurately estimate structural modal parameters and physical properties under random excitations. An experimental study on the north cable pylon of Sutong Bridge further verifies the accuracy and applicability of the proposed technique.更多还原