摘要
基于振动的结构健康监测的前提是从振动测试信号中提取结构模态参数。随机子空间方法是近年来发展起来的一种线性系统辨识方法,可以有效地从环境激励的结构响应信号中提取结构模态参数。在随机子空间识别方法中,确定系统的阶数是该方法的关键工作,稳定图方法是一种比较新颖的确定系统阶次的方法。但是随机子空间方法容易产生虚假模态,这也是随机子空间方法的一个主要缺陷。因此针对于这一缺陷提出了一种基于两阶段稳定图的随机子空间识别结构模态参数方法,该方法的基本思想是将在现场采集的结构的输出信号进行分段,将各段信号用随机子空间结合稳定图进行识别,然后将所有各段所识别的模态参数再一次用稳定图方法进行分析,得出结构的模态参数。最后用一三跨连续梁的数值模型对该方法进行验证,结果表明该方法具有良好的识别效果。
Vibration-based structural health monitoring usually needs to extract the vibration characteristics from operational vibration measurements. Stochastic subspace identification is a novel approach developed recent years. It can identify modal parameters of linear structure from ambient vibration of structure. The key issue in stochastic subspace identification is to gain the order of the system. Stabilization diagram is a novel approach to decide the order of the system. But stochastic subspace identification may yield false model. This is the main shortcoming of this method. This paper presents a method for two-stage stabilization diagram based stochastic subspace identification of structural modal parameters. The key part of this method is dividing the output signal of a structure into several segments and the stochastic subspace identification is used to each part of the output signal. Then the stabilization diagram is used to all the identified parameters of each part of the output signal. Then the false modes are distinguished and the real modes of structure are gained. The method is evaluated by the numerical simulation in a three-span continuous beam.
出处
《地震工程与工程振动》
CSCD
北大核心
2008年第3期47-51,共5页
Earthquake Engineering and Engineering Dynamics
基金
国家973项目(2002CB412709)
江苏省自然科学基金项目(BK2007549)
关键词
参数识别
动力特性
随机子空间
稳定图
parameter identification
dynamic characteristics
stochastic subspace identification
stabilization diagram
