Identification of modal parameters from measured input and output data using a vector backward auto-regressive with exogeneous model
Identification of modal parameters from measured input and output data using a vector backward auto-regressive with exogeneous model
复制标题
使用外生模型的向量后向自回归从测量的输入和输出数据中识别模态参数
DOI：
10.1016/j.jsv.2003.08.020
复制
发表时间：
2004
影响因子：
4.7
通讯作者：
Yen
中科院分区：
文献类型：
--
作者：
C. Hung;W. Ko;Yen
提出了一种基于外生模型的矢量反向自回归（VBARX）模态识别系统。该模型是向量反向自回归（VBAR）模型的扩展。这两种后向模型在选择物理模式时都提供了同样的好处，因为它们都可以提供一个确定的边界，将系统模式与伪模式分开。VBAR模型可以仅从输出数据中识别结构参数。在某些情况下，如果输入数据可用，则扩展模型VBARX模型比VBAR模型提供了额外的优势。在本研究中，将VBARX模型转换为由测量输入和输出数据导出的等效状态空间模型。因此，利用等效状态空间模型可以准确地估计结构模态参数。最后给出了两个模态识别实例，验证了VBARX方法的有效性。(1)三自由度下的数值模拟数据。具有各种类型输入数据和各种噪声水平的动态系统。
This paper proposes a modal identification system based on vector backward auto-regressive with exogeneous (VBARX) model. The model is an extension of vector backward auto-regressive (VBAR). Both the backward models offer the same benefits in selecting physical modes, since both can provide a determinate boundary that separates system modes from spurious modes. The VBAR model can identify the structural parameters from only output data. In some circumstances, if the input data are available, the extended model, VBARX model, provides an additional advantage over the VBAR model. In this study, an equivalent state-space model derived from measured input and output data is transformed from the VBARX model. Consequently, the structural modal parameters can be estimated accurately using the equivalent state-space model. Two examples of modal identification are presented to demonstrate the availability and effectiveness of the proposed VBARX method. (1) Numerical data simulated in a 3-d.o.f. dynamic system with various types of input data and various noise levels. (2) Experimental data obtained from the National Center for Research on Earthquake Engineering (NCREE) in Taiwan, concerning five-story 1 2 -scale steel structure under a shaking table test.