基于感兴趣区域的螺栓位姿及尺寸检测研究
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山东交通学院船舶与港口工程学院 威海 264210

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TP391;TN911.73

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Research on bolt pose and size detection based on region of interest
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School of Naval Architecture and Port Engineering, Shandong Jiaotong University,Weihai 264210, China

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    摘要:

    为了提高工业生产中螺栓定位抓取的效率和准确性,提出基于感兴趣区域的螺栓位姿及尺寸检测方法。首先利用YOLOv5目标识别算法对螺栓目标进行识别,将识别出的目标区域截取为感兴趣区域。再利用中值滤波和二值化方法对ROI进行预处理,采用Canny改进算法检测目标轮廓。通过最优拟合直线算法获取螺栓的倾斜角度,并用矩特征算法求解出螺栓重心位置。最后采用霍夫两直线段最短距离算法检测螺栓直径。经过实验验证采用YOLOv5目标识别算法的识别准确率达到92.7%,螺栓倾斜角度的检查误差为±1.2°,螺栓直径的检测误差率为±5.5%,实现了对螺栓位姿和尺寸的识别。

    Abstract:

    In order to improve the efficiency and accuracy of bolt positioning and grasping in industrial production, a bolt pose and size detection method based on region of interest was proposed. Firstly, YOLOv5 target recognition algorithm is used to identify the bolt target, and the identified target area is intercepted as the region of interest. Then the ROI region is preprocessed by median filtering and binarization, and the Canny improved algorithm is used to detect the target contour. Then the bolt tilt Angle is calculated based on the best fitting line algorithm, and the bolt center of gravity is calculated by the moment feature algorithm. Finally, the shortest distance algorithm of Hough two straight line segments was used to detect the bolt diameter. After experimental verification, the recognition accuracy of YOLOv5 target recognition algorithm reaches 92.7%, the inspection error of bolt tilt Angle is ±1.2°, and the detection error rate of bolt diameter is ±5.5%, which realizes the identification of bolt pose and size.

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戴先鑫,付振山,马栋,孔飞一,屈家辉.基于感兴趣区域的螺栓位姿及尺寸检测研究[J].电子测量技术,2024,47(8):134-140

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  • 在线发布日期: 2024-07-15
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