Enhanced Multivariate Based Approach for SHM Using Hilbert Transform
In structural health monitoring, features extraction from measured data plays an important role. In order to enhance information about damage, we propose in this paper, a new damage detection methodology, based on the Hilbert transform and multivariate analysis. Using measurements given by distributed sensors of a smart composite structure, we apply the Hilbert transform to calculate an envelope matrix. This matrix is then treated using multivariate analysis. The subspaces associated to the envelope matrix are used to define a damage index (DI). Furthermore, from perturbation theory of matrices, we propose a bound associated to this DI, by inspecting this bound, decision on the health of the structure is generated. Experimentation on an actual composite smart structure will show the effectiveness of the proposed approach.
How to Cite
Multivariate analysis, Hilbert transform, angle between subspaces, perturbation theory of matrices, singular value decomposition, Smart composite strcuture
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