摘要
针对止血钳裙边冲裁工作效率低、劳动强度大、危险系数高等问题,提出了一种基于视觉定位的止血钳裙边冲裁机器人上料方法。搭建了机器视觉试验台,通过纠偏基准图像逆向采集策略完成图像采集,对图像进行预处理并运用亚像素方法提高边缘精度;通过模板匹配的方法获取止血钳抓取件位与基准位的位置偏差,并进行位置纠偏,最后由机器人将止血钳送至冲床凹模完成上料。试验结果表明,机器人自动上料的定位成功率可达96%以上,可满足止血钳裙边冲裁机器人自动上料的需求,平均日冲压量可达15000件,显著提高了冲压效率。研究内容可为冲床自动上料提供技术支持。
For the problems of low feeding efficiency,high labor intensity and high risk coefficient in the hemostatic forceps skirt edge trimming,a robot feeding method of hemostatic forceps skirt edge trimming based on visual positioning was proposed.The machine vision test platform was built,and the image acquisition was completed by the reverse acquisition strategy of correction reference image,then the image was preprocessed,whose edge accuracy was improved by the sub-pixel method.The position deviation between gripping position of hemostatic forceps and reference position was obtained by the template matching method,and the position deviation was corrected.Finally,the robot sent the hemostatic forceps to the die to complete the feeding.The experimental results show that the positioning success rate of the robot automatic feeding can reach more than 96%,which can meet the demand of the robot automatic feeding of hemostatic forceps skirt edge trimming.The average daily stamping capacity can reach 15000 pieces,and the stamping efficiency can be significantly improved.Thus,the research content can provide technical support for the automatic feeding of punch press.
作者
李蕾
杨振宇
李玉胜
刘发英
Li Lei;Yang Zhenyu;Li Yusheng;Liu Faying(School of Mechanical Engineering,Shandong University of Technology,Zibo 255000,China;Department of Mechanical Engineering,Binzhou Technician College,Binzhou 256600,China;Shandong Industrial-intelligent Science&Technology Co.,Ltd.,Zibo 255000,China;School of Electrical and Electronic Engineering,Shandong University of Technology,Zibo 255000,China)
出处
《锻压技术》
北大核心
2025年第5期211-218,共8页
Forging & Stamping Technology
基金
山东省科技型中小企业创新能力提升工程项目(2023TSGC0981)。
关键词
止血钳
裙边冲裁
图像处理
视觉定位
机器人上料
hemostatic forceps
skirt edge trimming
image processing
visual positioning
robot feeding
作者简介
李蕾(1991-),男,硕士研究生,E-mail:boxinglilei@163.com;通信作者:杨振宇(1973-),男,工学博士,副教授,E-mail:05338@163.com。
