基于改进MCSSD的时变系统模态参数识别

Modal Parameter Identification of Time-varying System Based on Improved Multi-scale Chirplet Sparse Signal Decomposition

对于参数时变的多自由度系统,基于多尺度线性调频原子稀疏信号分解及多项式相位信号参数估计理论,提出一种时变系统的模态参数识别方法。该方法先对多自由度时变振动系统响应信号划分二进制动态时间支撑区并形成多尺度线性调频原子库,再按时间支撑区顺序提取节点频率,最后根据单模态响应信号的包络和瞬时频率估计值识别系统的模态频率。刚度和阻尼线性变化与周期变化2种情况下的参数识别仿真算例表明,所提出的方法具有较高的识别精度和重要的工程应用前景。

For the multi degree of freedom system with time-varying parameters,a method for modal parameters identification of time-varying systems is proposed based on multi-scale chirplet sparse signal decomposition(MCSSD)and polynomial phase signal parameter estimation theory.In this method,the vibration response of the multi-degree-of-freedom linear time-varying system is divided into binary regions of dynamic time supporting and the multi-scale chirp basis function library is formed.Then the node frequency is extracted in order of the dynamic regions.The modal frequency of the system can be identified by using the envelope and instantaneous frequency of the single-mode vibration response.The numerical simulation examples of linear or periodic changing of stiffness and damping show that this method has high identification certainty and engineering application prospect.