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作 者:孙台炜 杨萍[1] 张玉杰[2] SUN Taiwei;YANG Ping;ZHANG Yujie(School of Electronic Information and Artificial Intelligence,Shaanxi University of Science&Technology,Shaanxi 710021,China;School of Electrical and Control Engineering,Shaanxi University of Science&Technology,Shaanxi 710021,China)
机构地区:[1]陕西科技大学电子信息与人工智能学院,陕西710021 [2]陕西科技大学电气与控制工程学院,陕西710021
出 处:《自动化与仪表》2025年第2期18-22,31,共6页Automation & Instrumentation
基 金:陕西省重点研发计划项目(2023-YBGY-208)。
摘 要:冲压过程中经常由于冲压件表面出现异物导致冲压模具损坏。如果依靠人力观察,实时性不能保证的同时漏检率还高。为解决上述问题,设计了基于机器视觉的冲压过程监视系统。根据冲压监视系统需求,设计了系统结构并对视觉设备进行选型。采用基于模板匹配的冲压件异物检测算法,通过多模板粗匹配算法、ORB精匹配配准算法以及冲压件异物检测等进行异物检测。通过设计冲压过程检测软件界面并分配线程资源完成软件构建。测试表明,系统实际检出率可达99.8%,算法对于每幅待测图像的平均处理耗时在85 ms左右,满足冲压检测准确性与实时性的需求,实现冲压过程监视自动化管理。The stamping die is often damaged due to foreign bodies on the surface of the stamping part during the stamping process.If relying on manual observation,not only the real-time can not be guaranteed but also results in high omission rates.To address these issues,the stamping process monitoring system based on machine vision is designed in this paper.According to the requirements of the stamping monitoring system,the system structure was designed,and the vision equipment was selected.Foreign object detection algorithm for stamped parts based on template matching was adopted.The detection algorithm was carried out using a multi-template coarse matching algorithm,ORB precise matching registration algorithm,and other related techniques.The stamping process detection software interface was designed,and thread resources were allocated to complete the software construction.The tests show that the system's actual detection accuracy can reach 99.8%,and the average processing time for each image to be tested is about 85 ms,meeting the requirements for stamping detection accuracy and real-time performance,thus achieving automated management of the stamping process monitoring.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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