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Combining empirical wavelet transform and transfer matrix or modal superposition to reconstruct responses of structures subject to typical excitations

机译:组合经验小波变换和转移矩阵或模叠重建典型激励的结构响应

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摘要

An investigation is presented in this paper into the applicability of empirical wavelet transform, combined with mode transfer matrix and/or modal superposition, to reconstruction of responses of structures subject to typical excitations. Empirical wavelet transform, of which the parameters are determined from scale-space representation, is used to decompose each measured response signal into a number of mono-components. Structural responses at unmeasured locations are reconstructed from those mono-components, either through superposition of normal modes, or through mode transfer matrices, both derived from a finite element model of the structure in question. The method is applied to a high-speed train-used extruded aluminium panel subject to typical excitations. Considered excitations include impact excitations, stochastic excitations, periodic excitations and periodic impact excitations. The accuracy of the method is demonstrated both numerically and experimentally. The robustness of the method to measurement noise is also investigated for the panel. Results show that the proposed method is not only able to overcome difficulties in existing methods caused by shortages in measurement point, mode mixing and/or periodic excitations, but also robust to measurement noise.
机译:本文提出了一种对经验小波变换的适用性,与模式转移矩阵和/或模态叠加相结合,重建结构典型激动的结构的反应。经验小波变换,其中参数由比例空间表示确定,用于将每个测量的响应信号分解为多个单一组件。通过叠加正常模式,或通过模式传输矩阵来重建未测量位置的结构响应,或通过模式传输矩阵来自所讨论的结构的有限元模型。该方法应用于经过典型激励的高速列车用过的挤出铝面板。被认为激动包括影响激发,随机激发,周期性激励和定期影响激发。该方法的准确性在数字和实验上进行了说明。对于面板,还研究了对测量噪声的方法的稳健性。结果表明,该方法不仅能够在测量点,模式混合和/或周期性激发中造成的现有方法中的困难,而且还能够克服造成的方法,而是对测量噪声的鲁棒。

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