基于多尺度线调频基稀疏信号分解的时变系统模态参数识别

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

在多尺度线调频基稀疏信号分解的基础上,提出一种时变系统的模态参数识别方法。该方法先采用多尺度线调频基稀疏信号分解方法对多自由度线性时变振动系统响应信号进行分解,将其分解成多个单模态振动响应信号并得到单模态振动响应信号的瞬时频率;再根据单模态振动响应信号的包络和瞬时频率识别系统的模态频率与模态阻尼比。多自由度线性时变振动系统模态参数的识别算例表明,与经验模态分解等时频分析方法比较,该方法能有效克服系统振动响应信号分解时的模态混淆问题,识别精度高,抗噪性能好,是一种有较大工程应用前景的多自由度线性时变振动系统模态参数识别方法。

Based on the multi-scale chirp let sparse signal decomposition （MCSSD）, a method for modal parameters identification of time-varying systems is proposed. In the proposed method, the MCSSD method is used to decompose the vibration responses of a multi-degree-of-freedom linear time-varying system into several single-mode vibration responses, at the same time; the corresponding instantaneous frequency of each single-mode vibration response can be obtained. By using the envelope and instantaneous frequency of the single-mode vibration response, the system modal frequency and modal damping ratio can be identified. Compared with the empirical mode decomposition and other time-frequency analysis methods, the proposed method has strong noise immunity and high identification accuracy, further more, the mode confusion problem in decomposing the vibration response can be eliminated. Simulation example of the modal parameters identification of a multi-degree of freedom linear time-varying system shows the effectiveness and accuracy of the proposed method.