【摘要】 为提高结构模态参数的识别效率，解决随机子空间法(Stochastic Subspace Identification, SSI)中如虚假模态、模态混叠、定阶困难等问题，提出一种基于二阶盲识别算法(Secondary Order Blind Identification, SOBI)结合随机子空间法的模态参数识别方法。通过SOBI对多通道的振动信号进行盲源分离，得到单频或近似单频的模态响应时程，确定系统的阶次，然后通过快速傅里叶变换(Fast Fourier Transform, FFT)得到各阶模态响应的频谱图。设计一个具有特定通带特性的带通滤波器，使通带以外的其他频率成分抑制，从而提取出单一模态特征。最后，将只包含结构某一阶的模态信息输入到SSI中进行模态参数识别。结果表明，SOBI-SSI算法可有效剔除虚假模态和混叠模态，解决系统定阶问题，提高识别效率，且模态参数识别结果和SSI及有限元计算结果基本一致。更多还原

【Abstract】 In order to improve the identification efficiency of structural modal parameters and solve the problems such as false modes, mode aliasing and difficulty of order determination in SSI,a modal parameter identification method based on Secondary Order Blind Identification(SOBI) and Stochastic subspace identification was proposed.The blind source separation of multi-channel vibration signals was carried, by which the mode response time history of single frequency or approximately single frequency was obtained, and the order of the system was determined.After the spectral diagram of each mode response was obtained by Fast Fourier transform(FFT),a band-pass filter with specific passband characteristics was designed to suppress other frequency components outside the passband, so as to extract a single mode feature.Finally, the modal information containing only a certain order of the structure was input into SSI for modal parameter identification.The results show that SOBI-SSI algorithm can effectively eliminate false modes and aliasing modes, solve the problem of system order determination, improve the identification efficiency, and the modal parameter identification values are basically consistent with the results obtained by SSI and FEM.更多还原