测试技术学报2026，Vol.40Issue(3)：344-351,8.DOI:10.62756/csjs.1671-7449.2026022
基于YOLOv5算法的烟囱拆除机器人预留孔圆心定位模型
Chimney Demolition Robot Drilling Position Detection Model Based on YOLOv5
摘要
Abstract
The utilization of reserved holes on the chimney wall for the lifting and locking of the chimney demolition robot can significantly enhance the working efficiency of the robot.A method is proposed for identifying and locating reserved holes on the chimney wall based on deep learning object detection technol-ogy.Firstly,the YOLOv5 deep learning network model is used to detect the approximate area of the reserved holes in the image,obtaining the coarse positioning information of the reserved holes.Then,the Gaussian filtering method is applied to remove isolated points and noise in this area.Subsequently,based on the coarse positioning information of the reserved holes,the Canny operator is used to extract the edge information of the reserved holes.Finally,the least squares-based elliptical fitting method is employed to obtain the center coordinates of the reserved holes,achieving precise positioning of the reserved holes and effectively reducing the impact of factors such as blurred target edges,similar object interference,and cir-cular distortion on the positioning accuracy of the reserved holes.The research results show that the mAP@0.5%of the YOLOv5s model reaches 99.5%,with a detection speed of 6.5 ms.In the simula-tion environment,the center positioning error is less than 0.8 pixels,which can effectively improve the reliability and efficiency of the lifting operation of the chimney demolition robot.关键词
目标检测/YOLOv5算法/圆心定位/圆孔识别/机器视觉Key words
object detection/YOLOv5 algorithm/center alignment/circular hole recognition/machine vision分类
信息技术与安全科学引用本文复制引用
杨晨,吴亮,刘婵,安飞琴,李安国,师世博,赵俊生,王淋..基于YOLOv5算法的烟囱拆除机器人预留孔圆心定位模型[J].测试技术学报,2026,40(3):344-351,8.基金项目
山西省基础研究计划资助项目(202203021212158,20210302123039) （202203021212158,20210302123039）
