模态辨识中随机减量技术的实用改进

Practical Improvement of the Random Decrement Technique in Modal Identification

针对模态辨识实践中的随机减量加速度特征信号奇异值问题和结构实模态提取问题,提出相应的特征信号截断方法和最小距离法,改善结构模态辨识效果。首先,分析随机减量加速度特征信号的奇异值产生原因,提出特征信号截断方法,用于后续Ibrahim时域处理;其次,通过优化模型建立最小距离法的计算公式,便于从辨识所得复模态中提取结构实模态;最后,通过数值算例和结构模型实验,验证所提方法的可行性。结果表明:随机减量加速度特征信号的有效截断比例可取为1/200~1/50;最小距离法适用于各种类型响应下的结构实模态提取,抗噪能力强。

In view of the singular value problem of acceleration random decrement(RD)signature and the extraction problem of structural real mode shapes in the practice of modal identification,a corresponding signature truncation method and a minimum distance method are proposed to improve the modal identification effect.Firstly,the reason of the singular value of acceleration RD signature is analyzed,and the signature truncation method is proposed for the subsequent processing with the Ibrahim time domain technology.Then,by using an optimization model,the computation formula of the minimum distance method is established to facilitate the extraction of structural real mode shapes from the identified complex mode shapes.Finally,the numerical example and model experiment are applied to verify the feasibility of the proposed methods.The results show that a rational value of the truncation ratio for the acceleration RD signature would be 1/200~1/50,and the minimum distance method is applicable with high noise resistance for extracting real mode shapes under all kinds of responses.