Please use this identifier to cite or link to this item: https://doi.org/10.4018/978-1-59904-099-8.ch013
Title: Genetic algorithms in structural identification and damage detection
Authors: Koh, C.G. 
Perry, M.J.
Issue Date: 2006
Citation: Koh, C.G.,Perry, M.J. (2006). Genetic algorithms in structural identification and damage detection. Intelligent Computational Paradigms in Earthquake Engineering : 316-341. ScholarBank@NUS Repository. https://doi.org/10.4018/978-1-59904-099-8.ch013
Abstract: 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. © 2007, Idea Group Inc.
Source Title: Intelligent Computational Paradigms in Earthquake Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/84751
ISBN: 9781599040998
DOI: 10.4018/978-1-59904-099-8.ch013
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

2
checked on Mar 24, 2020

Page view(s)

96
checked on Mar 29, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.