现代电子技术2025，Vol.48Issue(6)：147-153,7.DOI:10.16652/j.issn.1004-373x.2025.06.022
基于双目视觉的桥式起重机吊钩定位系统研究
Research on bridge crane hook positioning system based on binocular vision
摘要
Abstract
In industrial production sites,crane machinery is widely used for material handling,and the potential damage to personnel safety and property is caused by its hooks during operation.In order to prevent these accidents,a YOLOv5 small target detection algorithm based on binocular vision is proposed.By combining the addition of objects and binocular vision,the fast and accurate positioning of the crane hook is realized.Four classical network models of YOLOv5 were trained and predicted respectively in OpenCV and Python environments,and on-site real-time data acquisition,error analysis and correction were carried out.The research results show that the single frame detection time of YOLOv5s model is 0.15 s,and the mAP value can reach 99.3%,which fully meets the requirements of real-time response and positioning accuracy on site.关键词
桥式起重机/起重机吊钩/双目视觉/YOLOv5/小目标检测/目标定位Key words
bridge crane/crane hook/binocular vision/YOLOv5/small target detection/target location分类
电子信息工程引用本文复制引用
高明科,陈薇,丁勇..基于双目视觉的桥式起重机吊钩定位系统研究[J].现代电子技术,2025,48(6):147-153,7.基金项目
国家重点研发计划资助项目(2022YFC3005502) （2022YFC3005502）
国家自然科学基金长江水科学研究联合基金项目(U2240221) （U2240221）
国家自然科学基金资助项目(51979174) （51979174）
