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Structural seismic damage detection using fractal dimension of time-frequency feature

  • School of Civil Engineering, Harbin Institute of Technology

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

Abstract

In this paper, a data-driven approach to localizing structural damage subjected to ground motion is proposed by using the fractal dimension of the time-frequency features of structural dynamic responses. The time-frequency feature is defined as the real part of wavelet coefficient and the fractal dimension adopts the box-counting method. It is shown that the proposed fractal dimensions at each story of linear system are identical, while the fractal dimension at the stories with nonlinearity is different from those at the stories with linearity. Therefore, the nonlinear behavior of structural damage caused by strong ground motions can be detected and localized through comparing the fractal dimensions of structural responses at different stories. Shaking table test on a uniform 16-story 3-bay steel frame with added friction dampers modelling interstory nonlinear behavior was conducted. The experiment results validate the effectiveness of the proposed method to localize single and multi seismic damage of structures.

Original languageEnglish
Title of host publicationStructural Health Monitoring
Subtitle of host publicationResearch and Applications
PublisherTrans Tech Publications Ltd
Pages554-560
Number of pages7
ISBN (Print)9783037857151
DOIs
StatePublished - 2013
Externally publishedYes
Event4th Asia-Pacific Workshop on Structural Health Monitoring - Melbourne, VIC, Australia
Duration: 5 Dec 20127 Dec 2012

Publication series

NameKey Engineering Materials
Volume558
ISSN (Print)1013-9826
ISSN (Electronic)1662-9795

Conference

Conference4th Asia-Pacific Workshop on Structural Health Monitoring
Country/TerritoryAustralia
CityMelbourne, VIC
Period5/12/127/12/12

Keywords

  • Fractal dimension
  • Friction damper
  • Modified force analogy method
  • Seismic damage detection
  • Time-frequency feature

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