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VISION-BASED FATIGUE CRACK DETECTION USING FEATURE TRACKING

机译:基于特征跟踪的基于视觉的疲劳裂纹检测

摘要

A computer-vision-based fatigue crack detection approach using a short video is described. Feature tracking is applied to the video for tracking the surface motion of the monitored structure under repetitive load. Then, a crack detection and localization algorithm is established to search for differential features at different frames in the video. The effectiveness of the proposed approach is validated through testing two experimental specimens with in-plane and out-of-plane fatigue cracks. Results indicate that the proposed approach can robustly identify fatigue cracks, even when the cracks are under ambient lighting conditions, surrounded by other crack-like edges, covered by complex surface textures, or invisible to human eyes due to crack closure. The approach enables accurate quantification of crack openings under fatigue loading with good accuracy.
机译:描述了使用短视频的基于计算机视觉的疲劳裂纹检测方法。将特征跟踪应用于视频,以跟踪重复荷载下受监视结构的表面运动。然后,建立裂缝检测和定位算法以搜索视频中不同帧的差异特征。通过测试两个带有面内和面外疲劳裂纹的实验样本,验证了所提方法的有效性。结果表明,即使裂纹在环境光照条件下,周围有其他裂纹状边缘,被复杂的表面纹理覆盖或由于裂纹闭合而肉眼看不见的情况下,所提出的方法仍可以可靠地识别疲劳裂纹。该方法能够以良好的精度对疲劳载荷下的裂纹开口进行精确定量。

著录项

  • 公开/公告号US2020284686A1

    专利类型

  • 公开/公告日2020-09-10

    原文格式PDF

  • 申请/专利权人 UNIVERSITY OF KANSAS;

    申请/专利号US201816768165

  • 发明设计人 JIAN LI;XIANGXIONG KONG;

    申请日2018-11-30

  • 分类号G01M5;

  • 国家 US

  • 入库时间 2022-08-21 11:20:29

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