American Journal of Engineering and Applied Sciences

Nondestructive Test Using a 3D Computer Vision System for Damage Detection of Structures

Taylor M.V. Szeto and Sun Yi

American Journal of Engineering and Applied Sciences

Abstract

Structures that do not have a definitive map nor a clearly known state of health may exist underground, beyond our reach and in unsuitable environments. Nuclear facilities contain underground tunnels that exhaust hazardous gases. Industry has miles of sewage lines beneath it that emit flammable and toxic gases. Regular inspection and maintenance is an essential part of failure prevention, however, these fatal environments have prohibited proper inspection of such infrastructure. Thus, the future of computer vision is vital to quality inspection. A strategically designed robot can be trained to visually inspect any structure, detect if there is a damage and decide if the damage is critical. Likened to any good inspector, the robot must be trained to investigate the nature of the damage and to alert the user of potential failures. This article discusses robotic training to detect damage in concrete structures and make decisions to the significance and impact of the defect.

Copyright

© 2018 Taylor M.V. Szeto and Sun Yi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.