基于改进随机子空间法的弧形闸门模态参数辨识

针对弧形闸门模态参数测试过程中存在的计算误差及环境激励干扰导致的虚假模态等问题,提出改进随机子空间法,即在弧形闸门模态参数辨识过程中引进随机子空间法,并利用时频分布——Gabor展开作为数据前处理,采用特征参数随数据量增加而变化的稳定图有效区分了物理模态和虚假特征,剔除虚假模态,辨识弱小特征,提高了辨识精度。以某水电站泄洪表孔弧形闸门为例进行模态参数辨识,并与有限元结果进行比较。结果表明,改进随机子空间法辨识结果与有限元数值分析结果吻合较好,可见所提方法可行、有效。

Modal Parameter Identification of Radial Gate Based on Stochastic Subspace Method

In view of the radial gate false modal parameters in the process of testing calculation error and environmental incentive interference problem, improved stochastic subspace method is put forward. The stochastic subspace method is introduced in the process of the radial gate modal parameter identification. And the time-frequency distribution and Gabor expansion are taken as the data pretreatment. The stability figure which characteristic parameters change with the increase of amount of data effectively distinguishes between physical modal and false features, eliminates the false modal, and identifies the weak characteristics. So, it improves the identification accuracy. Taking the radial gate of flood discharge crest outlet in a hydropower station as an example, modal parameter identification is carried out. Compared with finite element method, it shows that the results obtained by improved stochastic subspace method are in good agreement with the finite element numerical analysis. So, the proposed method is feasible and effective.