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A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

机译:基于计算机视觉的混凝土和沥青民用基础设施缺陷检测与状态评估研究进展

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摘要

To ensure the safety and the serviceability of civil infrastructure it is essential to visually inspect and assess its physical and functional condition. This review paper presents the current state of practice of assessing the visual condition of vertical and horizontal civil infrastructure; in particular of reinforced concrete bridges, precast concrete tunnels, underground concrete pipes, and asphalt pavements. Since the rate of creation and deployment of computer vision methods for civil engineering applications has been exponentially increasing, the main part of the paper presents a comprehensive synthesis of the state of the art in computer vision based defect detection and condition assessment related to concrete and asphalt civil infrastructure. Finally, the current achievements and limitations of existing methods as well as open research challenges are outlined to assist both the civil engineering and the computer science research community in setting an agenda for future research.
机译:为了确保民用基础设施的安全性和可维修性,必须目视检查和评估其物理和功能状况。这篇综述文章介绍了评估垂直和水平民用基础设施视觉状况的实践现状;特别是钢筋混凝土桥梁,预制混凝土隧道,地下混凝土管和沥青路面。由于土木工程应用的计算机视觉方法的创建和部署速度呈指数级增长,因此本文的主要部分全面介绍了基于计算机视觉的混凝土和沥青相关缺陷检测和状态评估的最新技术水平民用基础设施。最后,概述了现有方法的当前成就和局限性以及开放的研究挑战,以帮助土木工程和计算机科学研究界确定未来研究的议程。

著录项

  • 来源
    《Advanced engineering informatics》 |2015年第2期|196-210|共15页
  • 作者单位

    The University of Nottingham, Faculty of Engineering, Department of Civil Engineering, Room B27 Coates Building, University Park, Nottingham NG7 2RD, UK;

    Computing in Engineering, Ruhr-Universitaet Bochum, Universitaetstrasse 150, 44801 Bochum, Germany;

    Dept. of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States;

    Dept. of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States;

    Dept. of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Computer vision; Infrastructure; Condition assessment; Defect detection; Infrastructure monitoring;

    机译:计算机视觉;基础设施;条件评估;缺陷检测;基础设施监控;

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