一种高阶累积量的模态参数辨识方法改进及其应用

高阶累积量的模态参数辨识方法能够消除高斯噪声的影响。但基于传统的高阶累积量降阶方法的子空间模态参数辨识方法具有一定的缺陷。为此,提出2种降阶方法用于高阶累积量的子空间模态参数辨识方法,并对这2种方法进行了比较。利用主切片方法对某变截面轴进行了模态参数识别,获得了与有限元法相一致的计算结果,从而证明了该方法的可靠性。该方法的辨识质量较高,能够用于一般结构的模态参数辨识。

New identification method for modal parameter with high order cumlant and its application

A new identification method for the modal parameter with high order cumlant can be used to eliminate the effect from Gauss noise.But there are some deficiencies in the traditional subspace algorithm with high order cumlant.Two lower order algorithms for identifying subspace model parameter with HOC were put forward and then were coompared.The modal parameter of a section-variable shaft was identified with the mail slice algorithm and the result was consistent with that of the limit element analysis.The result proves that the method is effective and good in identification so that it can be used to identify a common structure of model parameters.