环境激励下基于信号降噪的模态参数识别研究

摘要

提出一种环境激励下基于测试信号降噪的模态参数识别方法。该方法首先对测试的随机响应数据采用自然激励技术（NExT）获得互相关函数，进而基于结构矩阵低秩逼近（SLRA）方法得到降噪后的信号，最后通过复指数（Prony）方法识别结构的模态参数。数值算例和模型实验结果表明，该方法对测量信号有很好的降噪作用，识别精度高。%A modal identification scheme based on signals denoised under ambient excitation was proposed here. With this method the natural excitation technique (NExT)was firstly applied to get the cross-correlation function for the measured random responses,and then the structured low rank approximation (SLRA)method was implemented to achieve the signals denoised.Finally,the modal parameters were estimated by using the complex exponential method (Prony’s method)from the noise-reduced signals.The effectiveness of the proposed method was verified by using numerical simulation and model tests.