Hankel matrix normalization for robust damage detection

Szymon Gres, Michael Döhler, Palle Andersen, Lars Damkilde, Laurent Mevel

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)
4 Downloads (Pure)

Abstract

In the context of detecting changes in structural systems, multiple vibration-based damage detection methods have been proposed and successfully applied to both mechanical and civil structures over the past years. One of the popular schemes is based on a robust subspace-based residual and enjoys favorable statistical and computational properties, like invariance to changes in the excitation covariance and numerical stability. This paper presents an alternative Gaussian residual that is based on the difference of normalized Hankel matrices between reference and damaged states, which can be easily computed. The statistical properties of the residual are reported and used for efficient hypothesis testing. Its robustness to excitation changes is shown. The proposed scheme is evaluated in numerical simulations, validating its robustness, and tested on real data sets from a full scale bridge.
Original languageEnglish
Title of host publicationProceedings of International Operational Modal Analysis Conference
EditorsSandro D. R. Amador, Rune Brincker, Evangelos I. Katsanos, Manuel Lopez Aenlle, Pelayo Fernandez
Number of pages8
Publication date2019
Pages147-154
ISBN (Electronic)9788409049004
Publication statusPublished - 2019
EventInternational Operational Modal Analysis Conference - København, Denmark
Duration: 13 May 201915 May 2019
http://iomac.eu/iomac-2019/

Conference

ConferenceInternational Operational Modal Analysis Conference
Country/TerritoryDenmark
CityKøbenhavn
Period13/05/201915/05/2019
Internet address

Keywords

  • Damage detection
  • Hankel matrix normalization
  • Hypothesis testing
  • Robust residual

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