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首页> 外文期刊>Mechanical systems and signal processing >Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping
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Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping

机译:在地震输入和高阻尼下通过改进的FDD算法对框架进行仅输出的模态动态识别

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摘要

The present paper deals with the seismic modal dynamic identification of frame structures by a refined Frequency Domain Decomposition (rFDD) algorithm, autonomously formulated and implemented within MATLAB. First, the output-only identification technique is outlined analytically and then employed to characterize all modal properties. Synthetic response signals generated prior to the dynamic identification are adopted as input channels, in view of assessing a necessary condition for the procedure's efficiency. Initially, the algorithm is verified on canonical input from random excitation. Then, modal identification has been attempted successfully at given seismic input taken as base excitation, including both strong motion data and single and multiple input ground motions. Rather than different attempts investigating the role of seismic response signals in the Time Domain, this paper considers the identification analysis in the Frequency Domain. Results turn-out very much consistent with the target values, with quite limited errors in the modal estimates, including for the damping ratios, ranging from values in the order of 1% to 10%. Either seismic excitation and high values of damping, resulting critical also in case of well-spaced modes, shall not fulfill traditional FFD assumptions: this shows the consistency of the developed algorithm. Through original strategies and arrangements, the paper shows that a comprehensive rFDD modal dynamic identification of frames at seismic input is feasible, also at concomitant high damping.
机译:本文通过改进的频域分解(rFDD)算法处理框架结构的地震模态动态识别,该算法在MATLAB中自主制定和实现。首先,仅对输出识别技术进行分析概述,然后用于表征所有模态特性。考虑到评估过程效率的必要条件,将动态识别之前生成的综合响应信号用作输入通道。最初,对来自随机激励的规范输入进行验证。然后,在给定的地震输入作为基础激励的情况下,已经成功尝试了模式识别,包括强运动数据以及单次和多次输入地面运动。与其尝试调查地震响应信号在时域中的作用,不如尝试在频域中进行识别分析。结果与目标值非常吻合,模态估计中的误差非常有限,包括阻尼比,其范围从1%到10%不等。无论是地震激励还是高阻尼值,即使在间隔良好的模式下也很关键,这些都不能满足传统的FFD假设:这表明了所开发算法的一致性。通过原始的策略和安排,本文表明在地震输入下,同时在高阻尼下,对框架进行全面的rFDD模态动态识别是可行的。

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