基于改进随机减量法和小波变换的

基于改进随机减量法和小波变换提出了一种新的结构模态参数统计识别方法.随机减量法改进后可直接处理零均值非平稳响应信号，得到自由衰减响应，小波变换的时频域特性可解耦密频、低阻尼系统，自助分布的统计估计能力考虑和降低模态参数识别的不确定性.对提出的方法进行了完整的理论推导，并通过一个四自由度系统的数值算例验证了该方法可靠性.相比较传统的时域方法和直接小波变换方法，该方法具有更高的识别精度，尤其是阻尼比系数.随后的抗噪能力验证结果表明该方法在15 dB 噪声干扰下仍能够稳定、准确地识别出系统的模态参数，可适用于环境激励下模态参数识别.
This paper presents a new statistical identification method for structural modal parameters based on the improved random decrement technique and wavelet transform. The improved random decrement technique is used to deal with zero mean non stationary signals directly for free decay responses. The wavelet transform is applied to decoupling dense frequency and low damping system because of its advantages in time frequency domain. The bootstrap procedure is employed to evaluate and decrease the uncertainty of the identification results. The reliability of the proposed method is validated by a four degree freedom numerical example. Compared with the traditional time domain method and the wavelet transform only method, the presented method has higher estimation accuracy, especially for damping ratios. Subsequent validation results for noise resistance show that the presented method is able to identify the modal parameters stably and precisely at the presence of 15dB measuring noise, which is applicable for structural modal parameter identification under environmental excitation