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Structural damage diagnosis of steel truss bridges by outlier detection

  • C. W. Kim
  • , S. Kitauchi
  • , K. C. Chang
  • , P. J. Mcgetrick
  • , K. Sugiura
  • , M. Kawatani
  • Kyoto University
  • Kobe University

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

11 Citations (Scopus)

Abstract

This study discusses structural damage diagnosis of real steel truss bridges by measuring trafficinduced vibration of bridges and utilizing a damage indicator derived from linear system parameters of a time series model. On-site damage experiments were carried out on real steel truss bridges. Artificial damage was applied to the bridge by severing a truss member with a cutting machine.Vehicle-induced vibrations of the bridges before and after applying damagewere measured and used in structural damage diagnosis of the bridges. Changes in the damage indicator are detected by Mahalanobis-Taguchi system (MTS) which is one of multivariate outlier analyses. The damage indicator and outlier detection was successfully applied to detect anomalies in the steel truss bridges utilizing vehicle-induced vibrations. Observations through this study demonstrate feasibility of the proposed approach for real world applications.

Original languageEnglish
Title of host publicationSafety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013
Pages4631-4638
Number of pages8
Publication statusPublished - 2013
Externally publishedYes
Event11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 - New York, NY, United States
Duration: 16 Jun 201320 Jun 2013

Publication series

NameSafety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013

Conference

Conference11th International Conference on Structural Safety and Reliability, ICOSSAR 2013
Country/TerritoryUnited States
CityNew York, NY
Period16/06/1320/06/13

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