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Validation of the uncertainty bounds on modal parameters identified with the SSI-COV method

Abstract

Applying the Covariance-driven Stochastic Subspace Identification method (SSI-COV) involves uncertainties in the numerical process of identifying modal parameters in a system. The main issue is that the method does not compute the uncertainty in the results, which is required in some problems such as outlier detection. Currently, one method is available to assess the uncertainty in modal parameters obtained using the SSI-COV. This method based on the sensitivity analysis of the modal parameters to perturbations in the collected data and is efficient but highly complex for its computational implementation. Thus, this article presents a validation of the uncertainty results obtained with this procedure through the uncertainty limits obtained using the Bootstrap technique. The validation is performed on the modal parameters of a numerical beam-type structure with controlled noise levels and the modal parameters of a concrete block of the Itaipu Hydroelectric Dam. The uncertainty limits obtained using the two methodologies showed similarities in the two examples, which allowed validating the sensitivity analysis procedure.

Keywords:
Uncertainty; bootstrap; sensitivity; modal parameter; identification

Graphical Abstract

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