Subspace-based Mahalanobis damage detection robust to changes in excitation covariance

Szymon Greś*, Michael Döhler, Palle Andersen, Laurent Mevel

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14 Citationer (Scopus)

Abstract

In the context of detecting changes in structural systems, several vibration-based damage detection methods have been proposed and successfully applied to both mechanical and civil structures over the past years. These methods involve computing data-based features, which are then evaluated in statistical tests to detect damages. While being sensitive to damages, the data-based features are affected by changes in the ambient excitation properties that potentially lead to false alarms in the statistical tests, a characteristic that renders their use impractical for structural monitoring. In this paper, a damage detection method is presented that is robust to changes in the covariance of the ambient excitation. The proposed approach is based on the Mahalanobis distance of output covariance Hankel matrices, which are normalized with respect to possibly changing excitation properties. The statistical properties of the developed damage feature are reported and used for efficient hypothesis testing. Its robustness towards changes in the excitation covariance is illustrated on numerical simulations and successfully tested on a numerical offshore foundation model.

OriginalsprogEngelsk
Artikelnummere2760
TidsskriftStructural Control and Health Monitoring
Vol/bind28
Udgave nummer8
ISSN1545-2255
DOI
StatusUdgivet - aug. 2021

Bibliografisk note

Publisher Copyright:
© 2021 John Wiley & Sons, Ltd.

Emneord

  • Subspace-based Mahalanobis damage detection robust to changes in excitation covariance
  • Damage detection
  • Excitation changes
  • Mahalanobis distance
  • Subspace-based methods

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