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Bridge deck delamination identification from unmanned aerial vehicle infrared imagery

机译:从无人机红外图像识别桥面分层

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摘要

The rapid, cost-effective, and non-disruptive assessment of bridge deck condition has emerged as a critical challenge for bridge maintenance. Deck delaminations are a common form of deterioration which has been assessed, historically, through chain-drag techniques and more recently through nondestructive evaluation (NDE) including both acoustic and optical methods. Although NDE methods have proven to be capable to provide information related to the existence of delaminations in bridge decks, many of them are time-consuming, labor-intensive, expensive, while they further require significant disruptions to traffic. In this context, this article demonstrates the capability of unmanned aerial vehicles (UAVs) equipped with both color and infrared cameras to rapidly and effectively detect and estimate the size of regions where subsurface delaminations exist. To achieve this goal, a novel image post-processing algorithm was developed to use such multispectral imagery obtained by a UAV. To evaluate the capabilities of the presented approach, a bridge deck mockup with pre-manufactured defects was tested. The major advantages of the presented approach include its capability to rapidly identify locations where delaminations exist, as well as its potential to automate bridge-deck related damage detection procedures and further guide investigations using other higher accuracy and ground-based approaches. (C) 2016 Elsevier B.V. All rights reserved.
机译:快速,经济高效且无中断地评估桥面状况已成为桥梁维护的一项严峻挑战。甲板分层是一种常见的变质形式,历史上已通过拖链技术进行评估,最近又通过无损评估(NDE)进行评估,包括声学和光学方法。尽管NDE方法已被证明能够提供与桥面脱层有关的信息,但许多方法耗时,劳动强度大,价格昂贵,而它们又需要对交通造成重大干扰。在这种情况下,本文演示了同时配备彩色和红外摄像机的无人机(UAV)能够快速有效地检测和估计存在地下分层的区域大小的能力。为了实现这一目标,开发了一种新颖的图像后处理算法,以使用通过无人机获得的这种多光谱图像。为了评估所提出方法的功能,测试了具有预制缺陷的桥面模型。所提出的方法的主要优点包括其能够快速识别分层的位置的能力,以及使桥面相关损伤检测程序自动化的潜力,并可以使用其他更高精度和基于地面的方法进一步指导研究。 (C)2016 Elsevier B.V.保留所有权利。

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  • 来源
    《Automation in construction》 |2016年第2期|155-165|共11页
  • 作者单位

    Drexel Univ, Dept Mech Engn & Mech, Philadelphia, PA 19104 USA;

    Drexel Univ, Dept Mech Engn & Mech, Philadelphia, PA 19104 USA;

    Rutgers State Univ, Dept Civil & Environm Engn, Piscataway, NJ 08854 USA;

    Drexel Univ, Dept Civil Architectural & Environm Engn, Philadelphia, PA 19104 USA;

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