基于信号时频分解的模态参数识别

给出了基于响应信号Gabor展开与重构的模态参数辨识的时频分析方法。通过响应信号的展开与重构，单频特征振动可从复杂的响应信号中分离出来，由它些特征振动信号可进一步提取系统物模态振动参数。论述了频率、阻尼和特征振型的估计方法以及估计方法对系统响应信号的特殊要求。此方法可适用于平衡、非平衡的响应信号，且无需输入信号，属于环境激励下的一种参数辨识方法。仿真结果说明明频展开与重构方法是模态参数辩识的有效手段之一。

Modal Parameter Identification Using Signal Decomposition in Time-Frequency Domain

A new method concerning modal parameter identification of linear time invariant systems is presented in this paper. In light of the Gabor theory of signal decomposition, responses of a multi degree of freedom system can be decomposed into uncoupled signals, vibrating at a single natural frequency. Given these uncoupled signals, parameter estimation can be subsequently conducted with common methods. Compared with traditional methods, the proposed approach requires no input signal except for response signals generated by unknown environmental excitation and no matter whether it is stationary or not. In the sense of less restriction on the in out signals, the approach based on signal decomposition in time frequency domain is very general. A numerical example of a simply supported beam under non stationary excitation is also presented to demonstrate the effectiveness of the proposed method.