摘要
未知激励下的土木工程结构响应信号通常是随机的且噪声水平较高,因此对其进行参数识别具有挑战性。从未知激励下的振动响应信号出发,结合随机减量技术、解析模态分解、希尔伯特变换和卡尔曼滤波理论提出一种新的未知激励下土木工程结构模态参数识别新方法。该方法首先采用随机减量技术将实测的振动响应信号转换成自由振动响应信号;其次,运用解析模态分解理论将转换后的自由振动响应信号分解成各阶独立的模态分量信号;最后,采用希尔伯特变换估计出各阶分量信号的固有频率和模态阻尼比。然后运用卡尔曼滤波算法对估算出的频率和阻尼比进行滤波和平滑以得到更精确的识别值。通过一个含有密集模态分量的合成信号和一个未知激励作用下4层钢框架结构试验验证了该方法的有效性,研究结果表明:该方法在未知激励情况下仍然能够准确有效识别结构固有频率和阻尼比。
Since the response signals of civil engineering structures under unknown excitations are usually non-station-ary and have a high noise level,it is a challenge to identify the parameters of the structures accurately and effectively.In this pa-per,a new method for the modal parameter identification of civil engineering structures with unknown excitations is proposed.This method is exactly a combination of random decrement technique,analytical mode decomposition,Hilbert transform,and Kalman filter.Firstly,the random decrement technique is used to transfer the measured vibration signals to the free vibration re-sponse signals.Then,the analytical mode decomposition is employed to decompose the free vibration response signals into in-dividual mode components.Finally,Hilbert transform is used to estimate the natural frequency and damping ratio of each mode and then Kalman filter is introduced to smooth the modal identification results.The effectiveness of the proposed method is val-idated via a synthetic signal including closely-spaced components and a test of four-story steel frame structure under an un-known excitation.The results demonstrate that the method can identify the natural frequencies and damping ratios accurately and effectively with unknown excitations.
作者
刘景良
俞安华
吴琛
盛叶
骆勇鹏
LIU Jingliang;YU Anhua;WU Chen;SHENG Ye;LUO Yongpeng(College of Transportation and Civil Engineering,Fujian Agriculture and Forestry University,Fuzhou 350002,China;College of Civil Engineering,Fujian University of Technology,Fuzhou 350118,China)
出处
《噪声与振动控制》
CSCD
2019年第6期6-12,230,共8页
Noise and Vibration Control
基金
国家自然科学基金青年基金资助项目(51608122)
中国博士后基金面上项目(2018M632561)
福建农林大学杰出青年科研人才计划项目(XJQ201728)
关键词
振动与波
解析模态分解
随机减量技术
参数识别
希尔伯特变换
卡尔曼滤波
vibration and wave
analytical mode decomposition
random decrement technique
parameter identification
Hilbert transform
Kalman filter
