电焊机2024，Vol.54Issue(4)：36-42,7.DOI:10.7512/j.issn.1001-2303.2024.04.05
基于3D视觉与深度学习的焊接钢管端部引熄弧板切割点空间定位方法
Spatial Positioning Method for Cutting Points of Tab Plate at the End of Welded Steel Pipes based on 3D Vision and Deep Learning
摘要
Abstract
A new cutting point spatial positioning method is proposed to address the current issues of low accuracy,slow speed,and poor environmental adaptability of the cutting point space positioning of the end quenching arc plate of welded steel pipes.This method first extracts effective point clouds and filters outliers from point clouds using a three-dimensional point cloud processing method,and projects them into a two-dimensional image using a two-dimensional image processing method;Then,the object detection method in deep learning is used to determine the edge area of the connection between the end of the steel pipe and the arc extinguishing plate in the two-dimensional image;Finally,calculate and analyze the intersec-tion information of the steel pipe end and the run on/off tab in the two-dimensional image and map the intersection Informa-tion mapping to the original three-dimensional point cloud to complete the spatial positioning of the cut point of the run on/off tab at the steel pipe end.Experimental tests were conducted on 896 different steel pipe ends with point cloud data(posi-tive samples)and 104 data without arcing plates(negative samples).The statistical test results showed that the accuracy of edge positioning between the positive sample tube end and the arcing plate connection reached 99.7%,the false detection rate was 0.0%,and the negative sample detection rate was 0.96%.The method used in this article was used to test the spatial position of the cutting point of the steel pipe end quenching arc plate 294 times.The comprehensive error between the test re-sults and the actual cutting point position was statistically analyzed,and the results were all within±2 mm.The average time for spatial positioning of the cutting point of the steel pipe end quenching arc plate was 5.8 seconds.The test results indicate that this method can effectively solve the above problems.关键词
引熄弧板/点云处理/图像处理/深度学习/空间定位Key words
tab plate/point cloud processing/image processing/deep learning/spatial positioning分类
矿业与冶金引用本文复制引用
石玮,周坤,刘福海,张焱,杨战利..基于3D视觉与深度学习的焊接钢管端部引熄弧板切割点空间定位方法[J].电焊机,2024,54(4):36-42,7.基金项目
哈尔滨焊接研究院有限公司技术创新发展基金(202216215) （202216215）
