基于模态缩减和模态实验数据的结构连接参数识别方法

利用在结构系统可测自由度上获得的不完备模态参数和子结构的有限元模型，根据模态缩减理论，建立了识别子结构间连接子结构参数的优化模型，采用逐次二次规划法求解，改善了测试噪声和模态截断误差的影响。该方法识别精度高、收敛速度快、计算量小，便于工程应用。

Identification of Joint Parameters Using Modal Reducing Method and Modal Experimental Data

Based on the modal reduction method, incorporating the substructure finite element model with the incomplete modal parameters measured from the assembled structure, an efficient method for the joint physical parameters identification is presented in this paper. In the process, the modal reduction method is employed to reduce the freedoms of assembled structures in order to decrease the amount of computation, the optimization model for sequence quadratic programming is established by treating the two norms of the frequency difference between the condensed model and the measured frequency as the objective function, the sensitivity matrix of eigenvalues as the gradient vectors, and parts of eigenvectors as constraints. The numerical example shows that the presented procedure can successfully identify the joint parameters from modal parameters with noise for condensed model.