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

    Research output: Chapter in Book/Report/Conference proceedingChapter

    7 Citations (Scopus)
    380 Downloads (Pure)


    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
    EditorsGeorge Deodatis, Bruce R. Ellingwood, Dan M. Frangopol
    Place of PublicationNew York
    PublisherCRC Press
    Number of pages8
    ISBN (Print)9781138000865
    Publication statusPublished - 10 Feb 2014

    Fingerprint Dive into the research topics of 'Structural damage diagnosis of steel truss bridges by outlier detection'. Together they form a unique fingerprint.

    Cite this