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Identification of modal parameters of a time invariant linear system by continuous wavelet transformation

机译：连续小波变换识别时不变线性系统模态参数

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摘要

The applications of wavelet transforms have received significant attentions in many fields. This work proposes a procedure for identifying modal parameters of a linear system using the continuous wavelet transform. The merits of the proposed procedure over the exiting schemes of applying the wavelet transform to system identification for a linear system are in use of the time invariance property and filtering ability of the transform to enhance the efficiency of identifying the modal parameters of a structure from its earthquake responses or free vibration responses. The effectiveness and accuracy of the proposed procedure are validated via numerical simulations. The effects of noise and wavelet function on identifying the modal parameters of the structure are also explored in processing the numerically simulated acceleration responses of a six-story shear building subjected to base excitation. The dynamic characteristics of close modes are accurately determined. Finally, the proposed procedure is adopted to obtain the modal parameters of a three-story non-symmetric steel frame from its measured acceleration responses in a shaking table test. A total of nine modes are identified, including modes with high frequencies and very small amplitude.
机译：小波变换的应用已在许多领域引起了广泛的关注。这项工作提出了一种使用连续小波变换识别线性系统模态参数的程序。相对于将小波变换应用于线性系统的系统识别的现有方案而言，所提出程序的优点在于利用了时不变性和变换的滤波能力，从而提高了从结构的模态参数识别结构的效率。地震响应或自由振动响应。通过数值模拟验证了所提方法的有效性和准确性。在处理受基础激励的六层剪切建筑物的数值模拟加速度响应时，还探讨了噪声和小波函数对识别结构的模态参数的影响。精确确定关闭模式的动态特性。最后，在振动台试验中，采用拟议的程序，从其测得的加速度响应中获得了三层非对称钢框架的模态参数。共识别出九种模式，包括具有高频率和非常小的振幅的模式。

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