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The role of modal parameters uncertainty estimation in automated modal identification, modal tracking and data normalization
Highlights Modal identification of a concrete arch dam with uncertainty quantification. Continuous dynamic monitoring of a concrete arch dam. Consideration of modal parameters estimates uncertainties within modal tracking processing. Elimination of outliers and parasite frequencies. Comparison between regular and weighted regression models in the minimization of external effects on modal properties.
Abstract During the last decade, many vibration-based structural health monitoring systems have been successfully implemented in different structures such as bridges, towers, stadia and wind turbines, with the aim of studying the structure dynamics and its evolution over time, eventually detecting the occurrence of novel structural behaviour that may indicate the presence of damage. Such vibration-based monitoring systems generally rely on the identification of modal properties, which are then used as monitoring features. Therefore, from operational modal analysis to the tracking of those features and finally to data normalization, many processing steps occur that depend on the accuracy of the identified modal properties. Thus, the estimation of the uncertainties associated with the identified modal properties increases the robustness of this process. In this context, data obtained from the continuous dynamic monitoring of a concrete arch dam has been used to evaluate the gains of quantifying the uncertainties of modal properties, evaluating in particular the effect of taking these uncertainties into consideration when performing automated operational modal analysis, modal tracking and data normalization. Nevertheless, it is observed that the most significant gains of considering estimates uncertainties occur when these quantities are used for removing outliers during modal tracking.
The role of modal parameters uncertainty estimation in automated modal identification, modal tracking and data normalization
Highlights Modal identification of a concrete arch dam with uncertainty quantification. Continuous dynamic monitoring of a concrete arch dam. Consideration of modal parameters estimates uncertainties within modal tracking processing. Elimination of outliers and parasite frequencies. Comparison between regular and weighted regression models in the minimization of external effects on modal properties.
Abstract During the last decade, many vibration-based structural health monitoring systems have been successfully implemented in different structures such as bridges, towers, stadia and wind turbines, with the aim of studying the structure dynamics and its evolution over time, eventually detecting the occurrence of novel structural behaviour that may indicate the presence of damage. Such vibration-based monitoring systems generally rely on the identification of modal properties, which are then used as monitoring features. Therefore, from operational modal analysis to the tracking of those features and finally to data normalization, many processing steps occur that depend on the accuracy of the identified modal properties. Thus, the estimation of the uncertainties associated with the identified modal properties increases the robustness of this process. In this context, data obtained from the continuous dynamic monitoring of a concrete arch dam has been used to evaluate the gains of quantifying the uncertainties of modal properties, evaluating in particular the effect of taking these uncertainties into consideration when performing automated operational modal analysis, modal tracking and data normalization. Nevertheless, it is observed that the most significant gains of considering estimates uncertainties occur when these quantities are used for removing outliers during modal tracking.
The role of modal parameters uncertainty estimation in automated modal identification, modal tracking and data normalization
Pereira, Sérgio (Autor:in) / Reynders, Edwin (Autor:in) / Magalhães, Filipe (Autor:in) / Cunha, Álvaro (Autor:in) / Gomes, Jorge P. (Autor:in)
Engineering Structures ; 224
03.08.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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