This paper presents an enhanced version and the validation of a recently proposed methodology for earthquake-induced damage detection and localization in masonry towers by using long-term vibration monitoring data. The proposed enhanced method is based on continuous operational modal analysis through stochastic subspace identification, dynamic multiple linear regressive analysis to remove the effects of changing environmental conditions and finite element (FE) model updating. Any anomalous frequency deviation from normal conditions resulting from an earthquake triggers the damage localization process. This task is performed by solving an inverse FE model calibration problem, where equivalent elastic properties of macrostructural elements are identified by minimizing an objective function considering experimentally identified and numerically predicted damage-induced decays in natural frequencies and changes in eigenvector components. To minimize the computational effort of this calibration procedure, a quadratic surrogate model is constructed using a tuned numerical FE model of the structure. The methodology is validated through application to the “Sciri Tower”, an historic civic masonry tower located in Perugia, Italy, that has been continuously monitored by the authors for more than 1 year. The validation is carried out by using simulated damage scenarios and a set of real far-field earthquake data and is based on a FE model of the tower including surrounding buildings, calibrated on the basis of the measured data from ambient vibration tests. The results demonstrate that the proposed procedure is capable of correctly detecting and localizing earthquake-induced damages.

Earthquake-induced damage localization in an historic masonry tower through long-term dynamic monitoring and FE model calibration

Venanzi I.
;
Kita A.;Cavalagli N.;Ierimonti L.;Ubertini F.
2020

Abstract

This paper presents an enhanced version and the validation of a recently proposed methodology for earthquake-induced damage detection and localization in masonry towers by using long-term vibration monitoring data. The proposed enhanced method is based on continuous operational modal analysis through stochastic subspace identification, dynamic multiple linear regressive analysis to remove the effects of changing environmental conditions and finite element (FE) model updating. Any anomalous frequency deviation from normal conditions resulting from an earthquake triggers the damage localization process. This task is performed by solving an inverse FE model calibration problem, where equivalent elastic properties of macrostructural elements are identified by minimizing an objective function considering experimentally identified and numerically predicted damage-induced decays in natural frequencies and changes in eigenvector components. To minimize the computational effort of this calibration procedure, a quadratic surrogate model is constructed using a tuned numerical FE model of the structure. The methodology is validated through application to the “Sciri Tower”, an historic civic masonry tower located in Perugia, Italy, that has been continuously monitored by the authors for more than 1 year. The validation is carried out by using simulated damage scenarios and a set of real far-field earthquake data and is based on a FE model of the tower including surrounding buildings, calibrated on the basis of the measured data from ambient vibration tests. The results demonstrate that the proposed procedure is capable of correctly detecting and localizing earthquake-induced damages.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1459410
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