基于提升小波包和模糊模式识别的结构有限元模型修正

Finite element model updating of structure based on lifting wavelet packet transform and fuzzy pattern recognition

提出了基于提升小波包特征提取和模糊模式识别的结构有限元模型修正方法。该方法首先建立以节点固结系数表示的空间网架单元刚度矩阵,然后利用提升框架,将结构振动测试信号进行提升小波包分解,提取小波包信号分量能量作为特征向量,以此建立模糊模式识别的模糊子集,最后利用模糊模式识别方法对结构进行有限元模型修正,并研究了噪声对该算法的影响。为了证明该方法,对一个二层网架结构模型进行了数值仿真,结果表明该方法能够有效地修正结构的有限元模型。

The finite element model correction method of truss structure based on lifting wavelet packet transform and fuzzy pattern recognition was presented. The element stiffness matrix of spatial truss was established using the joint fixity factor. The vibration signal was decomposed by using lifting wavelet packet （WP） analysis based on lifting scheme, and then the corresponding characteristic vector was established in the light of the lifting WP component energy, which can be used as the subset of fuzzy pattern recognition. Finally, the finite element model was updated in accordance with the fuzzy pattern recognition, and the effect of noise on the algorithm was also studied. In order to verify the proposed method, the numerical analysis on a two-story truss structure model was carried out. The numerical results show that the proposed method can be effectively used to correct the finite element model.