Experimental examples for identification of structural systems using degree of freedom-based reduction method

Abstract

Identification method on various structural system has been introduced in many numerical ways to validate complex structures by FEM using experimentally measured data. The objection of this study is to figure out how to identify a perturbed structure model by comparing with measured data based on original FEM data. Identified structure will improve the accuracy and reality to the numerical model by minimizing those differences between two models. Base-line model (original model) is constructed by FEM and will be compared with perturbed model (real model) by IPM (Inverse Perturbation Method). Measured dynamic responses, which is eigenvalues and eigenvectors, will be applied to satisfy the equilibrium and minimize the difference of dynamic responses between base-line model and perturbed model. In experimental examples, due to lack of number of sensor locations which will be located on the model, condensation method is used to restore full model. The equilibrium equation is expressed in terms of measured (primary) and unmeasured (secondary) degree of freedom. In the present study, influence of selection of sensor location and the convergence are considered and selection of sensor algorithm is applied to identification method. Experimental examples demonstrate that the proposed method improves accuracy of identifying perturbed structure model.