Comparison of sparse representation and fourier discriminant methods: Damage location classification in indirect lab-scale bridge structural health monitoring

Z. Wang, S. Chen, G. Lederman, F. Cerda, J. Bielak, J. H. Garrett, P. Rizzo, J. Kovačević

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

Abstract

This paper presents a novel method for interpreting data to improve the indirect structural health monitoring (SHM) of bridges. The research presented in the study is part of an ongoing study aimed at developing a novel SHM paradigm for the health assessment of bridges. In this paradigm, we envision the use of an instrumented vehicle that assesses a bridge's dynamic characteristics while traveling across the bridge. These characteristics are then correlated to the health of the structure by means of advanced signal processing and pattern recognition approaches. In this paper, we present and compare two classification algorithms that locate the presence of damages at well-defined locations on the structure: sparse representation and the Fourier discriminant methods, and find that the sparse representation method provides superior classification accuracy.

Original languageEnglish (US)
Title of host publicationStructures Congress 2013
Subtitle of host publicationBridging Your Passion with Your Profession - Proceedings of the 2013 Structures Congress
PublisherAmerican Society of Civil Engineers (ASCE)
Pages436-446
Number of pages11
ISBN (Print)9780784412848
DOIs
StatePublished - 2013
EventStructures Congress 2013: Bridging Your Passion with Your Profession - Pittsburgh, PA, United States
Duration: May 2 2013May 4 2013

Publication series

NameStructures Congress 2013: Bridging Your Passion with Your Profession - Proceedings of the 2013 Structures Congress

Other

OtherStructures Congress 2013: Bridging Your Passion with Your Profession
CountryUnited States
CityPittsburgh, PA
Period5/2/135/4/13

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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