基于云-边缘协同计算的表面缺陷检测系统研究

基于现有表面缺陷检测系统所存在的实时检测难、硬件要求高等问题,提出一种基于云计算与边缘协同计算的表面缺陷检测系统。将轻量化改进后的 YOLOv4 缺陷检测算法模型部署到边缘端嵌入式设备中,在边缘端完成对表面缺陷的检测,并在边缘端和云端设备部署 KubeEdge 框架进行通信和管理。通过案例验证该系统不仅能够满足检测实时性的要求,还能够提取缺陷检测关键信息,同时便于部署在价格低廉的嵌入式设备。

Research on a Surface Defect Detection System Based on the Cloudedge Computing

Existing surface defect detection system has a series of problems such as the difficulty of real timedetection and the high hardware requirements.To solve these problems,a surface defect detection system is proposed using the cloudedge computing.The system deploys the lightweight YOLOv4 defect detection algorithm model to the edgeend embedded device,completes the detection of surface defects at the edgeend,and deploys the KubeEdge framework on the edge and cloud devices for communication and management.Through case verification,the proposed system can not only meet the requirements of realtime detection,but also extract key information about defect detection,and is easy to deploy in lowcost embedded devices.