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STRUCTURAL MODAL IDENTIFICATION USING AN IMPROVED EMPIRICAL MODE DECOMPOSITION

机译:使用改进的经验模态分解的结构模态识别

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Empirical mode decomposition (EMD) has shown significant promises in signal decomposition of vibration data of civil engineering structures. Owing to its self-adaptive time-frequency decomposition capability, it is widely used in system identification of both linear and nonlinear structures. Unlike EMD which uses only single sensor, multivariate EMD (MEMD) is recently explored as a modal identification tool utilizing multichannel vibration measurements. In this paper, the performance of MEMD is investigated by integrating with another powerful signal separation technique to undertake modal identification under a wide range of applications. The proposed EMD method is validated using a suite of numerical studies.
机译:经验模式分解(EMD)在土木工程结构振动数据的信号分解中显示出显着的承诺。由于其自适应时频分解能力,它广泛用于线性和非线性结构的系统识别中。与仅使用单个传感器的EMD不同,多变量EMD(MEMD)最近探讨了利用多通道振动测量的模态识别工具。在本文中,通过与另一种强大的信号分离技术集成来研究MEMD的性能,以在广泛的应用下进行模态识别。所提出的EMD方法使用套件进行验证。

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