Improved polyreference time domain method for modal identification using local or global noise removal techniques

Improved polyreference time domain method for modal identification using local or global noise removal techniques
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使用局部或全局噪声消除技术进行模态识别的改进多参考时域方法

DOI:
10.1007/s11433-011-4625-1
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发表时间:
2012-06
期刊:
Science China Physics,Mechanics & Astonomy
影响因子:
--
通讯作者:
HuaJun Li
HuaJun Li
中科院分区:
其他
文献类型:
--
作者:
Sau-Lon James Hu;Sau-Lon James Hu;XingXian Bao;XingXian Bao;HuaJun Li;HuaJun Li

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模态识别涉及从测量数据估计结构系统的模态参数,例如模态频率、阻尼比和模态形状。在测量了多个输入和输出位置的含噪脉冲响应信号的条件下,本文的主要目的是应用局部或全局噪声去除技术来改进基于多参考点时域(PTD)方法的模态识别。传统的PTD方法通过过度指定计算模型阶数来吸收噪声,从而提高了模态参数估计的精度。本文提出了一种在进行模态参数估计算法之前,使用实际系统阶数作为计算模型阶数并剔除大量噪声的方法。研究了两种噪声去除方法:一种是一次从一个信号中去除噪声的“局部”方法,另一种是同时去除多个测量信号噪声的“全局”方法。本文中的数值研究是基于两个测试装置的实验测量:3个输入和10个输出的悬臂梁,和4个输入和32个输出的悬挂板。本文证明了所提出的噪声抑制方法优于传统的噪声吸收PTD方法在几个关键方面。
Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response signals associated with multiple input and output locations have been measured, the primary objective of this study is to apply the local or global noise removal technique for improving the modal identification based on the polyreference time domain (PTD) method. While the traditional PTD method improves modal parameter estimation by over-specifying the computational model order to absorb noise, this paper proposes an approach using the actual system order as the computational model order and rejecting much noise prior to performing modal parameter estimation algorithms. Two noise removal approaches are investigated: a “local” approach which removes noise from one signal at a time, and a “global” approach which removes the noise of multiple measured signals simultaneously. The numerical investigation in this article is based on experimental measurements from two test setups: a cantilever beam with 3 inputs and 10 outputs, and a hanged plate with 4 inputs and 32 outputs. This paper demonstrates that the proposed noise-rejection method outperforms the traditional noise-absorption PTD method in several crucial aspects.
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