摘要
针对激励未知情况下,运行模态分析容易遗漏真实模态和产生虚假模态的问题,提出了基于特征系统实现算法的多参考点稳定图算法.该算法通过设置不同的参考点,利用自然激励技术结合特征系统实现算法识别模态参数,以阻尼比、基于输出矩阵的一致模态指标和模态置信度作为判别指标,确定可信度最高的模态参数.运用该算法和增强频域分解法对大跨度斜拉桥———崖门大桥的实测数据进行识别分析.结果表明,文中算法能准确地识别出低阶模态参数,能为有限元模型修正提供良好的基础.
As it is easy for the operational modal analysis with unkown excitation to miss true modes and produce spurious modes, an improved multiple reference degrees of freedom(DOFs) stabilization diagram algorithm is proposed based on eigensystem realization algorithm. In this algorithm, by setting different reference DOFs in each group of data, the modal parameters are identified by means of the natural excitation technique in junction with the eigensystem realization algorithm. Then, the most accurate modal parameters are determined with damping ratio, observability matrix-based consistent mode indicator and modal amplitude coherence as the identification indexes. Finally, the proposed algorithm and the enhanced frequency domain decomposition method are both evaluated by means of the modal identification of the measured data of a long-span cable-stayed bridge, the Yamen Bridge. The results show that the proposed algorithm is capable of accurately identifying the low modes, thus providing a good basis for finite element model updating.
出处
《华南理工大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2011年第9期41-47,53,共8页
Journal of South China University of Technology(Natural Science Edition)
基金
广东省交通运输厅科技项目(2010-02-015)
关键词
斜拉桥
运行模态分析
多参考点稳定图
自然激励技术
特征系统实现算法
增强频域分解
cable-stayed bridge
operational modal analysis
multiple reference DOFs stabilization diagram
natural excitation technique
eigensystem realization algorithm
enhanced frequency domain decomposition