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New methodology for modal parameters identification of smart civil structures using ambient vibrations and synchrosqueezed wavelet transform

机译:利用环境振动和同步小波变换的智能土木结构模态参数识别新方法

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Many applications related to modeling, control and condition assessment of smart structures require an accurate identification of natural frequencies and damping ratios. This identification is generally carried out through artificial and natural vibration sources. The latter is often preferred in many situations; yet their analysis represents a challenge since the measured data are non-stationary with a high noise level. In this paper, a new methodology is proposed based on the synchrosqueezed wavelet transform (SWT). First, the random decrement technique (RDT) is applied to estimate the free vibration response from measured ambient vibration signals. Then, the SWT algorithm is used to decompose the vibration response into individual mode components. Finally, the Hilbert transform (HT) and the Kalman filter (KF) are used to estimate the natural frequencies and damping ratios of each mode and to filter and smoothen the results. The effectiveness of the proposed approach is first validated through numerical simulation of damped free vibration response of a 3-degree of freedom (DOF) system with two closely-spaced frequencies. Then, numerical and experimental data of a benchmark 4-story 2×2 bay 3D steel frame structure subjected to ambient vibrations is analyzed. Finally, the natural frequencies and damping ratios of a real-life bridge located in Queretaro, Mexico are obtained. For comparison purposes, two recent and advanced signal processing techniques, the complete ensemble empirical mode decomposition (CEEMD) technique and the short-time multiple signal classification (ST-MUSIC) are also tested. Numerical and experimental results show accurate identification of the natural frequencies and damping ratios even when the signal is embedded in high-level noise demonstrating that the proposed methodology provides a powerful approach to estimate the modal parameters of a civil structure using ambient vibration excitations.
机译:与智能结构的建模,控制和状态评估有关的许多应用都需要准确识别固有频率和阻尼比。这种识别通常是通过人工和自然振动源进行的。在许多情况下,后者通常是首选。然而,由于测量数据不稳定且噪声水平高,因此他们的分析面临挑战。本文提出了一种基于同步压缩小波变换(SWT)的新方法。首先,应用随机减量技术(RDT)从测量的环境振动信号中估计自由振动响应。然后,使用SWT算法将振动响应分解为各个模式分量。最后,使用希尔伯特变换(HT)和卡尔曼滤波器(KF)估算每种模式的固有频率和阻尼比,并对结果进行滤波和平滑处理。首先通过具有两个紧密间隔频率的3自由度(DOF)系统的阻尼自由振动响应的数值模拟来验证所提出方法的有效性。然后,分析了基准4层2×2托架3D钢框架结构在环境振动下的数值和实验数据。最后,获得了位于墨西哥克雷塔罗的真实桥梁的固有频率和阻尼比。为了进行比较,还测试了两种最新的高级信号处理技术,完整的集成经验模式分解(CEEMD)技术和短时多信号分类(ST-MUSIC)。数值和实验结果表明,即使将信号嵌入到高电平噪声中,也可以准确识别固有频率和阻尼比,这表明所提出的方法提供了一种使用环境振动激励来估算土木结构模态参数的有效方法。

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