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EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations

机译:基于EEMD-MUSIC的自然频率识别分析使用人工和自然激励

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摘要

This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several factors as nonstationary effects, close modal frequencies, and noisy environments, which are common situations where several techniques reported in literature fail. The EEMD and MUSIC methods are used to decompose the vibration signal into a set of IMFs (intrinsic mode functions) and to identify the natural frequencies of a structure, respectively. The effectiveness of the proposed methodology has been validated and tested with synthetic signals and under real operating conditions. The experiments are focused on extracting the natural frequencies of a truss-type scaled structure and of a bridge used for both highway traffic and pedestrians. Results show the proposed methodology as a suitable solution for natural frequencies identification of structures from free and ambient vibration signals.
机译:本文提出了一种新的基于EEMD-MUSIC(集成的经验模式分解-多信号分类)的方法,该方法可以识别结构中的模态频率,范围包括由人工和自然激发产生的自由振动和环境振动信号,还考虑了多种因素作为非平稳效应,接近模态频率和嘈杂的环境,这是文献中报道的几种技术失败的常见情况。 EEMD和MUSIC方法分别用于将振动信号分解为一组IMF(固有模式函数)并识别结构的固有频率。所提出的方法的有效性已通过合成信号并在实际操作条件下得到验证和测试。实验着重于提取桁架式比例结构和用于公路交通和行人的桥梁的固有频率。结果表明,所提出的方法是从自由振动和环境振动信号中识别结构固有频率的合适解决方案。

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