一种新的固有频率跟踪及虚假频率剔除方法

针对时变参数辨识中常见的固有频率辨识和虚假频率剔除问题,引入了一种基于新信息准则的子空间跟踪辨识算法,结合实验提出了一种消除虚假固有频率的后处理方法。首先,利用基于新信息准则的子空间跟踪算法辨识出伪时变模态参数;其次,通过聚类方法估计各阶伪固有频率;最后,利用滑动的数据窗比对数据剔除虚假频率。该方法仅需要给出预估的活动模态数即可。不同频率变化形式的仿真算例结果证明了本研究方法较其他辨识算法在信号信噪比较低时具有较高的辨识精度。高温环境下的时变模态实验也验证了该方法的可行性,说明该方法在实际工程中具有较高的应用价值。

Novel Natural Frequency Tracking and Spurious Frequency Elimination Method

Considering the natural frequency estimation and spurious frequency elimination are common in time-varying modal parameter identification, a subspace tracking algorithm based on the novel information criterion is introduced. A post-process procedure for spurious modes elimination is proposed. Firstly, the pseudo modal parameters are obtained through the proposed subspace tracking identification method, then the fuzzy C-means clustering algorithm is implemented to acquire the initial pseudo natural frequencies, finally a moving data window is applied to select the pseudo natural frequencies by data comparison. The proposed validation method only needs an estimated active modes number. Numerical simulations with different frequency changing types in dicats that the proposed method can reach higher calculation accuracy. The identification and validation method are verified through a modal parameters identification of a time-varying structure in the high temperature environment. The experiment shows that the proposed method has high application value.