摘要
针对电缆护套断裂伸长率的人工测量方法精度差、自动程度低的缺陷,提出一种基于双目视觉的自动测量方法.首先采集试样拉伸视频,对首帧图像采用基于信息熵的算法定位2个圆环标记符圆心坐标,若正确识别则使用圆心坐标作为标记点,否则选取立体匹配结果良好的SURF特征点中距离圆心最近的点作为标记点;然后用金字塔L-K光流法追踪隔帧采样后的护套拉伸视频中的标记点,基于计算出的标记点三维坐标和加速度判定试样断裂的粗略帧位置,再回溯2个采样间隔进行逐帧检测,最终精确定位断裂帧并计算断裂伸长率.在电缆护套质检现场进行实验的结果表明,以240帧/s高速相机的测量结果作为真值,采用所提方法测得断裂伸长率的测量均方根误差为7.13%,低于人工测量方法的21.84%,处理速度达到了107.8帧/s,在实际应用中能明显提升检测的精度、速度和自动化程度.
In order to solve the problem of accuracy and automation of manual measurement for elongation at break of cable sheath,an automatic measurement based on binocular vision is proposed.Firstly,after the sample tensile video is collected,location method based on information entropy is used on the first frame for the center coordinates of two circle markers,if markers are correctly identified,the center coordinate is used as the marked point,otherwise the point closest to the center of circle in SURF feature points with good ste-reo matching results is selected as the marked point.Secondly,the marked points tracking based on L-K op-tical flow is used in the sampled video of sheath stretching process,the determination of the rough frame position of sheath breaking is based on the calculated three-dimensional coordinates and acceleration,then two sampling intervals are backtracked for frame by frame detection.Finally,the breaking frame is located precisely then elongation at break is calculated.The experimental results in the field of quality inspection of cable sheath show that the measured root mean square error of elongation at break is 7.13%which is lower than that of manual measurement method(21.84%),compared with the true values measured by 240 fps high-speed camera,and the processing speed of the method reaches 107.8 fps.Propose method can obviously improve the detection accuracy,speed and automation in practical application.
作者
张格悠
龚俊
陈俊松
张志东
朱策
刘凯
Zhang Geyou;Gong Jun;Chen Junsong;Zhang Zhidong;Zhu Ce;Liu Kai(College of Electrical Engineering,Sichuan University,Chengdu 610065;Chengdu Institute of Product Quality Inspection Co.,Ltd.,Chengdu 610199;CNPC Chuanqing Drilling Engineering Company Limited,Chengdu 610056;School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2021年第11期1668-1676,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金面上项目(61473198)
四川省科技厅重点研发项目(2020YFG0029).
关键词
双目视觉
三维重建
断裂伸长率
加速鲁棒特征
金字塔L-K光流
binocular vision
3D reconstruction
elongation at break
speeded-up robust features
pyramidal L-K optical flow
