[1]梁 程,薛建彬.基于云-边缘协同计算的表面缺陷检测系统研究[J].机械与电子,2022,(02):65-70.
 LIANG Cheng,XUE Jianbin.Research on a Surface Defect Detection System Based on the Cloud-edge Computing[J].Machinery & Electronics,2022,(02):65-70.
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基于云-边缘协同计算的表面缺陷检测系统研究()
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机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2022年02期
页码:
65-70
栏目:
自动控制与检测
出版日期:
2022-02-22

文章信息/Info

Title:
Research on a Surface Defect Detection System Based on the Cloud-edge Computing
文章编号:
1001-2257 ( 2022 ) 02-0065-06
作者:
梁 程薛建彬
南京航空航天大学机电学院,江苏 南京 210016
Author(s):
LIANG Cheng XUE Jianbin
( College of Mechanical and Electrical Engineering , Nanjing University of Aeronautics and Astronautics , Nanjing 210016 , China )
关键词:
云计算边缘计算表面缺陷检测深度学习算法
Keywords:
cloud computing edge computing surface defect detection deep learning algorithm
分类号:
TP183 ; TP391.41
文献标志码:
A
摘要:
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。
Abstract:
Existing surface defect detection system has a series of problems such as the difficulty of real-time detection and the high hardware requirements.To solve these problems , a surface defect detection system is proposed using the cloud-edge computing.The system deploys the lightweight YOLOv4 defect detection algorithm model to the edge-end embedded device , completes the detection of surface defects at the edge-end , 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 real-time detection , but also extract key information about defect detection , and is easy to deploy in low-cost embedded devices.

参考文献/References:

[ 1 ] 陶显,侯伟,徐德 . 基于深度学习的表面缺陷检测方法综述[ J ] . 自动化学报, 2021 , 47 ( 5 ): 1017-1034.

[ 2 ] WANG Y B , LIU M G , ZHENG P , et al.A smart surface inspection system using faster R-CNN in cloud edge computing environment [ J ] .Advanced engineering informatics , 2020 , 43 : 101037.1-101037.9.
[ 3 ] 尹子会,孟荣,范晓丹,李冰,赵振兵 . 融合边缘计算和改进 Faster R-CNN 的变电站设备典型视觉缺陷检测系统[ J ] . 中国科技论文, 2021 , 16 ( 3 ): 343-348.
[ 4 ] REDMON J , DIVVALA S , GIRSHICK R , et al.You only look once : unified , real-time object detection[ C ]// IEEE Conference on Computer Vision and Pattern Recognition , 2016 : 779-788.
[ 5 ] REN S Q , HE K M , GIRSHICK R , et al.Faster R-CNN : towards real-time object detection with region proposal networks [ J ] .IEEE Transactions on pattern analysis and machine intelligence , 2017 , 39 ( 6 ):1137-1149.
[ 6 ] WANG C Y , LIAO H Y M , WU Y H , et al.CSPNet : a new backbone that can enhance learning capability of CNN[ C ]//2020 IEEE / CVF Conference on Computer Vision and Pattern Recognition Workshops ( CVPRW ) .New York : IEEE , 2020 : 1571-1580.
[ 7 ] HE K M , ZHANG X Y , REN S Q , et al.Spatial pyramid pooling in deep convolutional networks for visual recognition [ J ] .IEEE Transactions on pattern analysis and machine intelligence , 2015 , 37 ( 9 ): 1904-1916.
[ 8 ] LIU S , QI L , QIN H F , et al.Path aggregation network for instance segmentation [ C ]// 2018 IEEE / CVF Conference on Computer Vision and Pattern Recognition( CVPR ), 2018 : 8759-8768.
[ 9 ] ZHENG Z H , WANG P , LIU W , et al.Distance-IoU Loss : faster and better learning for bounding box regression [ C ]//AAAI Conference on Artificial Intelli-gence , 2020 : 12993-13000.
[ 10 ] SHI W S , CAO J , ZHANG Q , et al.Edge computing : vision and challenges [ J ] .Internet of things journal ,IEEE , 2016 , 3 ( 5 ): 637-646.
[ 11 ] DING R W , DAI L H , LI G P , et al.TDD-Net : a tiny defect detection network for printed circuit boards[ J ] .CAAI Transactions on intelligence technology , 2019 , 4 ( 2 ): 110-116.

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备注/Memo

备注/Memo:
收稿日期: 2021-08-16
作者简介:梁 程 ( 1997- ),男,江苏扬州人,硕士研究生,研究方向为物联网、缺陷检测;薛建彬 ( 1970- ),男,江苏南京人,副教授,研究方向为机器人应用、智能化制造。
更新日期/Last Update: 2022-03-04