基于深度学习及5G+边缘云的AOI视觉检测系统设计与实现  

AOI Vision Inspection System Based on Deep Learning and 5G+Edge Cloud

作　　者：秦博 

机构地区：[1]广东中强精英电子科技有限公司,广东东莞523000 [2]西安极像技术有限公司,陕西西安710075

出　　处：《工业控制计算机》2025年第4期67-68,71,共3页Industrial Control Computer

摘　　要：介绍了一种基于深度学习以及5G+边缘云的AOI视觉检测系统的设计与实现。该系统利用深度学习算法对显示器产品进行缺陷检测,通过5G技术实现高速数据传输,结合边缘云进行实时数据分析和处理。实验结果表明,该系统能够快速、准确地检测出产品中的缺陷和瑕疵,漏检率≤0.3%,误判率<2%,单画面检测时间≤1 s,检测效率比传统的人工检测提高了10倍以上。同时,基于深度学习算法相较于传统算法,具备持续学习能力,可以有效保证系统的长期稳定、可靠和高效运行,不再需要针对不同产品进行规则设置,大幅度提高了生产效率。This paper introduces the design and implementation of an AOI vision inspection system based on deep learning and 5G+edge cloud.The system uses deep learning algorithm to detect defects in display products,realizes high-speed data transmission through 5G technology,and combines edge cloud for real-time data analysis and processing.The experimental results show that the system can quickly and accurately detect the defects and flaws in products,with a missed detection rate of≤0.3%,a misjudgment rate of<2%,a single screen detection time of≤1 second,and the detection efficiency is more than 10 times higher than that of traditional manual detection.At the same time,compared with the traditional algorithm,the algorithm based on deep learning has continuous learning ability,which can effectively ensure the long-term stable,reliable and efficient operation of the system,and it is no longer necessary to set rules for different products.

关 键 词：深度学习 5G 边缘云 AOI视觉检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]