Abstract
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.
Highlights
Due to technological advances in measurement devices and the development of methods for automatized operational modal analysis (OMA), it is nowadays possible to extract the dynamic characteristics of large civil structures under normal operating conditions from the response measurements caused by ambient vibrations
The organization of the paper is as follows: i) Section 2.1 introduces the SSI-COV method, ii) Section 2.2 presents the process of automatic estimation of the modal parameters, iii) Sections 3 explain the theory concerning the uncertainty approach from sensitivity analysis and bootstrap approach, and v) Section 4 reports the results of the validation of the two structures
The computational time used for the concrete block example was 30 seconds to obtain the standard deviations of all modes in the multi-order model and 5 seconds to get the modal parameters of each bootstrap time series, adding up to a total time of approximately 83 min for Bootstrap technique
Summary
Due to technological advances in measurement devices and the development of methods for automatized operational modal analysis (OMA), it is nowadays possible to extract the dynamic characteristics of large civil structures (such as buildings, bridges, and dams) under normal operating conditions from the response measurements caused by ambient vibrations. Reynders et al (2008) derived a numerical procedure to estimate the uncertainties of the modal parameters obtained at some given model order from the SSI-COV method to deal with that aspect. This paper reports the computation of confidence intervals on the modal parameters identified by using the SSICOV method for two civil structures Such estimations follow the uncertainty quantification approach proposed by (Reynders et al, 2008) and computationally improved by Döhler et al, (2013). The organization of the paper is as follows: i) Section 2.1 introduces the SSI-COV method, ii) Section 2.2 presents the process of automatic estimation of the modal parameters, iii) Sections 3 explain the theory concerning the uncertainty approach from sensitivity analysis and bootstrap approach, and v) Section 4 reports the results of the validation of the two structures.
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