Dof-based submatrix scaling factors for damage detection in reinforced concrete bridges

Kyeongtaek Park; Marco Torbol

doi:10.1117/12.2231061

20 April 2016 Dof-based submatrix scaling factors for damage detection in reinforced concrete bridges

Kyeongtaek Park, Marco Torbol

Proceedings Volume 9803, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2016; 980352 (2016) https://doi.org/10.1117/12.2231061
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2016, Las Vegas, Nevada, United States

Abstract

This study focuses on the system identification and the damage detection of reinforced concrete bridges using neural network algorithm, eigenvalue analysis and parallel computing. First, autoregressive coefficients (ARCs) of both temporal output and forced input of the real structure are computed. The ARCs are used for the eigen-system realization algorithm (ERA) to obtain the modal parameters of the structure. Second, the ARCs are utilized as the input variable of the neural network algorithm while the outputs are the submatrix scaling factors that contain information about the degeneration of each element and each mode within the element. However, the neural network algorithm requires training to output reliable results. The training is the most challenging task of this study and finite element analysis is used to compute the modal parameters of the model built around the neural network outputs. The model is compared with the ERA results to update the neural network coefficients. Due to the scale of the neural network used parallel computing is necessary to reduce the computational time to a reasonable amount.

Citation Download Citation

Kyeongtaek Park and Marco Torbol "Dof-based submatrix scaling factors for damage detection in reinforced concrete bridges", Proc. SPIE 9803, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2016, 980352 (20 April 2016); https://doi.org/10.1117/12.2231061

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