Abstract

Failures of civil structures, such as bridges, due to natural events or anthropic loads can generate significant social and economic impacts. As an alternative for the identification of damage in these structures, dynamic structural health monitoring has been proposed. This paper presents the experimental evaluation of three damage identification techniques on a full-scale footbridge. One of the evaluated techniques is based on damage localization vectors; a second technique is based on changes in the curvature of the modal shapes, while the third technique uses a numerical model and artificial neural networks for locating the damaged section. Five scenarios of controlled damage were induced in the footbridge. Output-only ambient vibration tests were performed at each damage state and the results of the identification techniques were analyzed. The three implemented techniques showed promising results for the numerical simulations, and two of these techniques produced satisfactory results in the experimental evaluation.

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