基于小波包变换的时间序列模型模态参数识别

提出了基于小波包变换的时间序列模型结构模态参数识别方法.该方法以线性的离散时间序列方程为基础,对结构的振动响应数据进行小波包变换分解,利用小波包函数的正交特性,建立量测点间的离散化运动方程,最后利用该离散化运动方程的系数矩阵,估算结构的模态参数(自振频率、阻尼比与振型).用数值模拟算例对此方法进行了验证,并与随机子空间识别方法结果进行了比较.结果表明,该方法可以正确地识别出结构的模态参数.

Modal parameter identification of the time series model based on wavelet packet transform

A method of modal parameter identification of the time series model by using wavelet packet transform is suggested which is based on linear discrete time series equation.The measured responses of a structure are first decomposed by wavelet packet transform.Appropriate discrete equations of motion for measured degrees of freedom are established from the transformed responses by using the orthonormality of the wavelet package function.Finally,the modal parameter of the structure can be extracted from the coefficient matrix of the established discrete equations of motion.A numerical study is performed to demonstrate the proposed technique and verify its accuracy.The results obtained are comparable with those previously obtained from the stochastic subspace identification.It is show that the proposed technique is reliable and efficient, which can be used to identify the modal parameter of structure quite effectively.