Damage location and quantification of a pretensioned concrete beam using stochastic subspace identification

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2017-04-19
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Micheli, Laura
Laflamme, Simon
Alipour, Alice
Ubertini, Filippo
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Sritharan, Sri
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Civil, Construction and Environmental EngineeringElectrical and Computer EngineeringCenter for Nondestructive Evaluation (CNDE)
Abstract

Stochastic subspace identification (SSID) is a first-order linear system identification technique enabling modal analysis through the time domain. Research in the field of structural health monitoring has demonstrated that SSID can be used to successfully retrieve modal properties, including modal damping ratios, using output-only measurements. In this paper, the utilization of SSID for indirectly retrieving structures’ stiffness matrix was investigated, through the study of a simply supported reinforced concrete beam subjected to dynamic loads. Hence, by introducing a physical model of the structure, a second-order identification method is achieved. The reconstruction is based on system condensation methods, which enables calculation of reduced order stiffness, damping, and mass matrices for the structural system. The methods compute the reduced order matrices directly from the modal properties, obtained through the use of SSID. Lastly, the reduced properties of the system are used to reconstruct the stiffness matrix of the beam. The proposed approach is first verified through numerical simulations and then validated using experimental data obtained from a full-scale reinforced concrete beam that experienced progressive damage. Results show that the SSID technique can be used to diagnose, locate, and quantify damage through the reconstruction of the stiffness matrix.

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This proceeding is published as Alessandro Cancelli, Laura Micheli, Simon Laflamme, Alice Alipour, Sri Sritharan, Filippo Ubertini, "Damage location and quantification of a pretensioned concrete beam using stochastic subspace identification", Proc. SPIE 10169, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2017, 1016917 (19 April 2017); doi: 10.1117/12.2261825. Posted with permission.

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Sun Jan 01 00:00:00 UTC 2017