Author
Listed:
- Rocío Porras Soriano
(Department of Civil and Building Engineering, Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain)
- Behnam Mobaraki
(Department of Civil and Building Engineering, Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain)
- José Antonio Lozano-Galant
(Department of Civil and Building Engineering, Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain)
- Santos Sanchez-Cambronero
(Department of Civil and Building Engineering, Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain)
- Federico Prieto Muñoz
(Department of Industrial Engineering, Universidad Francisco de Vitoria (UFV), 28223 Madrid, Spain)
- Juan José Gutierrez
(INECO, 28036 Madrid, Spain)
Abstract
In the last years, more and more studies have highlighted the advantages of complementing traditional master classes with additional activities that improve students’ learning experience. This combination of teaching techniques is specially advised in the field of structural engineering, where intuition of the structural response it is of vital importance to understand the studied concepts. This paper deals with the introduction of a new (and more encouraging) educational tool to introduce students intuitively to the dynamic response of structures excited with an educational shaking table. Most of the educational structural health monitoring systems use sensors to determine the dynamic response of the structure. The proposed tool is based on a radically different approach, as it is based on low-cost image-recognition techniques. In fact, it only requires the use of an amateur camera, a black background, and a computer. In this study, the effects of both the camera location and the image quality are also evaluated. Finally, to validate the applicability of the proposed methodology, the dynamic response of small-scale buildings with different typologies is analyzed. In addition, a series of surveys were conducted in order to evaluate the activity based on student´s satisfaction and the actual acquisition and strengthening of knowledge.
Suggested Citation
Rocío Porras Soriano & Behnam Mobaraki & José Antonio Lozano-Galant & Santos Sanchez-Cambronero & Federico Prieto Muñoz & Juan José Gutierrez, 2021.
"New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings,"
Sustainability, MDPI, vol. 13(7), pages 1-21, March.
Handle:
RePEc:gam:jsusta:v:13:y:2021:i:7:p:3695-:d:524679
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