Crack depth classification by ultrasonic measurement system with artificial neural network (ANN)
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Published:
Feb 23, 2018
Keywords:
surface crack; ultrasonic; artificial neural network (ANN); back-propagated model; mortar
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Abstract
Abstract
This technical article presents a newly developed test system for classification of surface cracks in reinforced concrete structures. With the developed system, the diffractedand reflected ultrasonic wave patterns can be obtained and used for the classification of surface cracks. The classification of surface cracks is achieved by an artificial neural network (ANN). The developed system was used to determine whether crack depth reaches reinforcing bar or not. The result of this study shows a remarkable capability of the developed system to classify the type of surface cracks according to their depths in relation to cover thickness.
This technical article presents a newly developed test system for classification of surface cracks in reinforced concrete structures. With the developed system, the diffractedand reflected ultrasonic wave patterns can be obtained and used for the classification of surface cracks. The classification of surface cracks is achieved by an artificial neural network (ANN). The developed system was used to determine whether crack depth reaches reinforcing bar or not. The result of this study shows a remarkable capability of the developed system to classify the type of surface cracks according to their depths in relation to cover thickness.
Article Details
Section
Research Articles
The published articles are copyright of the Engineering Journal of Research and Development, The Engineering Institute of Thailand Under H.M. The King's Patronage (EIT).