A one stage damage detection technique using spectral density analysis and parallel genetic algorithms

Maryam Varmazyar, Nicholas Haritos, Michael Kirley, Tim Peterson

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

2 Citations (Scopus)

Abstract

This paper describes a new global damage identification framework for the continuous/periodic monitoring of civil structures. In order to localize and estimate the severity of damage regions, a one-stage model-based Bayesian probabilistic damage detection approach is proposed. This method, which is based on the response power spectral density of the structure, enjoys the advantage of broadband frequency information and can be implemented on input-output as well as output-only damage identification studies. A parallel genetic algorithm is subsequently used to evolve the optimal model parameters introduced for different damage conditions. Given the complex search space and the need to perform multiple time-consuming objective function evaluations, a parallel meta-heuristic provides a robust optimization tool in this domain. It is shown that this approach is capable of detecting structural damage in both noisy and noise-free environments.

Original languageEnglish
Title of host publicationStructural Health Monitoring
Subtitle of host publicationResearch and Applications
Number of pages11
DOIs
Publication statusPublished - 26 Jul 2013
Externally publishedYes
EventAsia-Pacific Workshop on Structural Health Monitoring 2012 - RACV Club, Melbourne, Australia
Duration: 5 Dec 20127 Dec 2012
Conference number: 4th
https://eprints.usq.edu.au/22740/8/SHM2012.pdf (Call for Papers)

Publication series

NameKey Engineering Materials
Volume558
ISSN (Print)1013-9826

Workshop

WorkshopAsia-Pacific Workshop on Structural Health Monitoring 2012
Abbreviated titleAPWSHM 2012
Country/TerritoryAustralia
CityMelbourne
Period5/12/127/12/12
OtherProceedings were published in
Key Engineering Materials:
Structural Health Monitoring: Research and Applications
scientific.Net
Internet address

Keywords

  • Bayesian probabilistic approach
  • Damage identification
  • Parallel genetic algorithm
  • Power spectral density
  • Severity

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