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首页> 外文期刊>Structural health monitoring >Concrete crack detection through full-field displacement and curvature measurements by visual mark tracking: A proof-of-concept study
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Concrete crack detection through full-field displacement and curvature measurements by visual mark tracking: A proof-of-concept study

机译：通过视觉标记跟踪通过全场位移和曲率测量来检测混凝土裂缝：概念验证研究

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摘要

In this study, a noncontact vision-based sensing method is proposed to measure surface displacements and curvatures and to detect cracks in a reinforced concrete slab. The proposed method includes five independent modules for structure boundary identification by a dynamic programming algorithm, boundary movement tracking by a contour tracking algorithm, distinguishable surface feature detection by speed-up-robust features, feature (visual mark) tracking by a three-stage data association algorithm, and displacement interpolation from those at visual marks by a Delaunay triangu-lation algorithm. The displacement field was used to evaluate the slab curvature that functioned as a crack indicator. The proposed data association algorithm for visual mark translation, linking, and connection was successfully applied for visual mark tracking of concrete slab images. The proposed algorithms used in five modules are computationally efficient, making them viable tools for real-time structural health monitoring. By persistently tracking the features and positions of spatially distributed visual marks in time-lapse videos, the displacement time histories at mark locations are successfully evaluated. The relative error of displacement measurements for the tested concrete slab is approximately 1.24%. The proposed method was applied to successfully detect cracks of a full-scale reinforced concrete slab from image analysis. Unlike contact measurements, the proposed noncontact measurement is not affected by concrete cracking.
机译：在这项研究中，提出了一种基于非接触式视觉的传感方法来测量表面位移和曲率并检测钢筋混凝土板中的裂缝。所提出的方法包括五个独立模块，用于通过动态编程算法识别结构边界，通过轮廓跟踪算法跟踪边界运动，通过提速鲁棒特征进行可区分的表面特征检测，通过三阶段数据进行特征（视觉标记）跟踪关联算法，并使用Delaunay三角算法从视觉标记处进行位移插值。位移场用于评估用作裂纹指示器的板曲率。所提出的视觉标记转换，链接和连接的数据关联算法已成功应用于混凝土板图像的视觉标记跟踪。在五个模块中使用的拟议算法在计算上是高效的，使其成为用于实时结构健康监测的可行工具。通过持续跟踪延时视频中空间分布的视觉标记的特征和位置，可以成功评估标记位置的位移时间历史。被测混凝土板位移测量的相对误差约为1.24％。提出的方法被用于通过图像分析成功地检测出全尺寸钢筋混凝土板的裂缝。与接触测量不同，建议的非接触测量不受混凝土开裂的影响。

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