Structural damage identification based on multi-objective optimization

Abstract

Structural damage identification is an inverse problem, which often is formulated as an optimization problem. The design variables are degrees of damage in computational model, and the objective is the discrepancies between the computed responses and the measured responses. Conventional single-objective optimization approach defines the objective function by combining multiple error terms into a single one, which leads to a weaker constraint in solving the identification problem. An alternative approach explained in this paper is a multi-objective approach that simultaneously minimizes multiple error terms. A stronger constraint from multiple objectives promotes the solutions to converge to the correct solution. Numerical examples based on static testing are provided to illustrate the multi-objective approach. Also, conceptual explanations are given to extend the approach to include both the static testing and the dynamic testing. Expected challenges will also be explained. ©2010 Society for Experimental Mechanics Inc.