Cointegration and the Empirical Mode Decomposition for the Analysis of Diagnostic Data

Abstract:

The use of cointegration has been proposed recently as a potentially powerful means of removing confounding influences from structural health monitoring (SHM) data. On the other hand the Empirical Mode Decomposition method is a recent multi-scale decomposition technique with the ability to decompose a signal into meaningful signal components. In this paper the EMD method will be used to highlight the dominant time-scales that have been affected by varying environmental and operational conditions and the time-scales that are related to damage. Then cointegration will be used to remove the nonstationary effects not associated with damage at the time-scales of interest in the data. The final step of the damage detection approach proposed, will be the use of two different amplitude-frequency separation methods, the Hilbert Transform and the more recent Teager Kaiser energy operator approach in order to compare the merits of both, concerning the estimation of the instantaneous characteristics of the signals.

• Periodical: Key Engineering Materials (Volumes 569-570)
• Pages: 884-891
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.569-570.884
• Online since: July 2013
• Authors: Ifigeneia Antoniadou, Elizabeth J. Cross, Keith Worden
• Keywords: Co-Integration, Empirical Mode Decomposition (EMD), Hilbert Transform, Teager-Kaiser Energy Operator

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