摘要
特征系统实现算法是近年来出现的时域模态参数识别技术。本文首先研究了该算法对混有白噪音的加速度及位移自由响应信号的识别特性,并发现辊速度信号和位移信号分别对系统的高频模态和低频模态敏感;然后结合算法的高速识别特点及滑动时间窗技术,研究了算法对振动水平的跟踪能力,并在此基础上提出识别混叠频率的方法;最后将该算法推广至利用常力强迫响应数据进行模态参数的情况,导出了相应的算法,并进行了算例验证。
The Eigensystem Realization Algorithm (ERA), as a model parameter identification method in time-domain has received more and more attention in recent years. In this paper, the characteristics of the algorithm for identification of displacement and acceleration data in free vibration at the presence of the white noise is studied and compared. It is found that the displacement data and the acceleration data are sensitive to the lower and higher modes respectively when the standard ERA is employed for identification. The tracing capability of the algorithm to the vibration level of the system is also studied with the aid of the sliding window technique, and a method for identifying aliasing frequency is established. In addition, the ERA is extended to the parameter identification of a system with constantly forced response data. The corresponding formulations are presented and verified with several examples.
出处
《工程力学》
EI
CSCD
北大核心
2002年第1期109-114,共6页
Engineering Mechanics
基金
自然基金(19802010)
863-2-2-4-1B资助项目
