摘要
为了从大型悬索桥的脉动实验结果得出精确的结构动力特性,以便进行结构的抗风、抗震研究和实时监测,本文利用随机子空间系统识别方法对虎门悬索桥进行了模态分析。这种时域识别方法基于状态空间模型,仅利用结构输出反应,避免了传统的人工识别和迭代过程,但必须利用稳定图形确定模型阶数。同有限元数值计算结果作比较后可看出,该法能识别出10个频率在0.5Hz以下的自振频率,并且可得到较好的结构阻尼,说明随机子空间系统识别方法是分析大型桥梁脉动实验特征参数的有力工具。
A stochastic subspace system identification method is used to extract modal parameter of HUMEN suspension bridge in order to get accurate structural dynamic characteristics from ambient experiment. The results are essential for structural anti-wind, aseismatic and real time monitoring. With the response data of ambient vibration, this time domain identification method can extract structural modal parameters based on the state space model, avoiding conventional manual identification and iterative process. But the stabilization diagram must be used to determine the modal sequences. Comparing to FEM numerical analysis, the method proposed in this paper can identify ten modes below 0.5 Hz and reliable damping ratio. Therefore, it is concluded that the stochastic subspace system identification method is a powerful tool to acquire the characteristic parameters of long-span bridges.
出处
《工程力学》
EI
CSCD
北大核心
2002年第4期46-49,共4页
Engineering Mechanics
基金
国家自然科学基金(49871065)
高校博士学科点专项基金(98000325)
关键词
随机子空间
系统识别
悬索桥
模态分析
脉动实验
有限元
stochastic subspace
system identification
suspension bridge
modal analysis
ambient experiment
