韩建平, 郑沛娟. 环境激励下基于快速贝叶斯FFT的实桥模态参数识别[J]. 工程力学, 2014, 31(4): 119-125. DOI: 10.6052/j.issn.1000-4750.2012.07.0560
引用本文: 韩建平, 郑沛娟. 环境激励下基于快速贝叶斯FFT的实桥模态参数识别[J]. 工程力学, 2014, 31(4): 119-125. DOI: 10.6052/j.issn.1000-4750.2012.07.0560
HAN Jian-ping, ZHENG Pei-juan. MODAL PARAMETER IDENTIFICATION OF AN ACTUAL BRIDGE BY FAST BAYESIAN FFT METHOD UNDER AMBIENT EXCITATION[J]. Engineering Mechanics, 2014, 31(4): 119-125. DOI: 10.6052/j.issn.1000-4750.2012.07.0560
Citation: HAN Jian-ping, ZHENG Pei-juan. MODAL PARAMETER IDENTIFICATION OF AN ACTUAL BRIDGE BY FAST BAYESIAN FFT METHOD UNDER AMBIENT EXCITATION[J]. Engineering Mechanics, 2014, 31(4): 119-125. DOI: 10.6052/j.issn.1000-4750.2012.07.0560

环境激励下基于快速贝叶斯FFT的实桥模态参数识别

MODAL PARAMETER IDENTIFICATION OF AN ACTUAL BRIDGE BY FAST BAYESIAN FFT METHOD UNDER AMBIENT EXCITATION

  • 摘要: 近年来,贝叶斯理论逐步应用于工程结构的模态参数识别、有限元模型修正及状态评估等方面。基于快速贝叶斯FFT的模态参数识别方法是针对某一共振频率带的单个模态,通过一个四维的数值优化问题得到模态参数的最佳估计,并通过对数似然函数关于模态参数的二阶导数求得Hessian矩阵,使得基于贝叶斯的参数识别方法可以快速高效地进行。为了评估该方法在实际桥梁结构模态参数识别应用中的可行性及优越性,运用快速贝叶斯FFT方法对环境激励下一刚构-连续组合梁桥的竖向加速度响应进行了分析处理,识别了其模态参数的最佳估计,并根据模态参数的变异系数评估了其后验的不确定性。识别结果与随机子空间识别结果的对比表明,两种方法识别的频率和振型基本吻合,阻尼识别结果的差异仍然较大。

     

    Abstract: The Bayesian theory is adopted in modal parameter identification, finite element model updating and condition assessment of the structures recently. Bayesian modal identification can be preformed quickly using Fast Bayesian FFT method where most probable values (MPVs) are obtained by solving at most a four-dimensional numerical optimization and Hessian matrix is calculated by second derivatives of log-likelihood function with respect to modal parameters for a single modal in a selected resonant frequency band. In this paper, in order to evaluate its feasibility and superiority for modal parameter identification of actual bridges, Fast Bayesian FFT method is adopted to process the vertical acceleration response of a rigid frame-continuous girders bridge under ambient excitation. In addition to the best estimates of modal parameters, their posterior uncertainties were also assessed by their coefficients of variation. Comparison with the results from stochastic subspace identification (SSI) indicates that identified modal frequencies and mode shapes agree very well, but the variation of the identified modal damping ratios is still high.

     

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