Genetic algorithms (GA) have proved to be a robust, efficient search technique for many problems. In this chapter, the latest developments by the authors in the area of structural identification and structural damage detection using genetic algorithms are presented. A GA strategy involving a search space reduction method (SSRM) using a modified genetic algorithm based on migration and artificial selection (MGAMAS) is first used to identify structural properties in multiple degree-of-freedom systems. The SSRM is then incorporated in a structural damage detection strategy using response measurements both before and after damage has taken place. Numerical studies on 10 and 20 degree-of-freedom systems show that a small damage of only 2.5% can be accurately and consistently identified from incomplete acceleration measurements in the presence of 5% input and output noise.

Introduction

Engineering analysis can be broadly categorized as direct analysis and inverse analysis. Direct analysis for structural systems aims to predict structural response (output) for given excitation (input) and known system parameters, whereas inverse analysis deals with identification of structural parameters based on given input and output (I/O) information. The latter may be termed as "structural identification" and falls within the larger domain of system identification. Structural identification can be applied to update or calibrate structural models so as to better predict response and achieve more cost-effective designs. It can also be used for structural health monitoring and damage assessment in a nondestructive way by...