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首页> 外文期刊>American journal of engineering and applied sciences >Nondestructive Test Using a 3D Computer Vision System for Damage Detection of Structures
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Nondestructive Test Using a 3D Computer Vision System for Damage Detection of Structures

机译:使用3D计算机视觉系统进行结构破坏检测的无损检测

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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.
机译:没有明确地图或没有明确已知健康状态的结构可能存在于地下,我们无法及无法承受的环境中。核设施包含排放有害气体的地下隧道。工业下面有数英里的排污管线,它们排放出易燃和有毒气体。定期检查和维护是预防故障的重要部分,但是,这些致命的环境禁止对此类基础结构进行适当的检查。因此,计算机视觉的未来对于质量检查至关重要。可以对经过战略设计的机器人进行培训,以使其目视检查任何结构,检测是否有损坏并确定损坏是否严重。与任何好的检查员相比,必须对机器人进行培训,以调查损坏的性质并警告用户潜在的故障。本文讨论了机器人培训,以检测混凝土结构中的损坏并决定缺陷的重要性和影响。

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