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
Source: 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
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