Damage detection through genetic and swarm-based optimization algorithms

B. H. Koh, J. H. Choi, M. J. Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

An experimental verification of damage detection process using some of novel optimization techniques such as Latin hypercube sampling and swarm-based algorithms is presented. The algebraic differences between damage variables of numerical model and the test structures are formulated as an objective function which has to be minimized to identify damage location and its severity in the process of model updating. The profiles of modal frequency shifts become damage-sensitive features in conjunction with structural or damage variables such as mass or stiffness of numerical model. The iterative process which exploits the proposed population-based optimization algorithms successfully identifies local mass changes by updating damage variables to fit in modal data from test structures such as cantilevered beam and multi-bay truss frame.

Original languageEnglish
Title of host publicationEarth and Space 2010
Subtitle of host publicationEngineering, Science, Construction, and Operations in Challenging Environments - Proceedings of the 12th International Conference
Pages2330-2335
Number of pages6
DOIs
StatePublished - 2010
Event12th International Conference on Engineering, Science, Construction, and Operations in Challenging Environments - Earth and Space 2010 - Honolulu, HI, United States
Duration: 14 Mar 201017 Mar 2010

Publication series

NameProceedings of the 12th International Conference on Engineering, Science, Construction, and Operations in Challenging Environments - Earth and Space 2010

Conference

Conference12th International Conference on Engineering, Science, Construction, and Operations in Challenging Environments - Earth and Space 2010
Country/TerritoryUnited States
CityHonolulu, HI
Period14/03/1017/03/10

Keywords

  • Algorithms
  • Damage
  • Model studies
  • Monitoring
  • Optimization

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