Application of YOLO Object Detection Network in Weld Surface Defect Detection
文献类型：会议论文
| 作者 | Zuo, Yinlong1; Wang JT(王金涛)2; Song JL(宋吉来)2 |
| 出版日期 | 2021 |
| 会议日期 | July 27-31, 2021 |
| 会议地点 | Jiaxing, China |
| 页码 | 704-710 |
| 英文摘要 | As industrial production becomes more modern and intelligent today, the inspection of product quality of the workshop is becoming more and more accustomed to replacing the old manual visual inspection methods with automated inspection systems. In the welding field, automated welding robots are not only used in traditional large-scale automobile assembly lines. In more general welding work, welding robots also plays an important role. The inspection of the welding quality of the welding robot is mainly to detect the four main types of weld defects. Compared to traditional defect classification based on support vector machines and defect detection based on template matching, this paper uses a welding surface defect detection system designed based on deep learning methods. By working with workshop welding experts, a large-scale image of nearly 5000 pictures is built. Large-scale weld defect datasets, while using the real-time and accuracy of the YOLO series of deep learning object detection frameworks, the weld defects detection model reaches 75.5% mean average precision(mAP) in constructed weld defect data set. In addition, the construction cost of the detection model and the deployment time of the detection system are greatly reduced. During the field test of the system in the workshop, among a batch of welding workpieces provided by the factory, the detection accuracy of weld defects reached 71%, which initially met the requirements of the workshop for an automated defect detection system. © 2021 IEEE. |
| 源文献作者 | IEEE Robotics and Automation Society ; Shenyang Institute of Automation CAS ; Shenzhen Academy of Robotics |
| 产权排序 | 2 |
| 会议录 | 2021 IEEE 11th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISSN号 | 2642-6633 |
| ISBN号 | 978-1-6654-2527-8 |
| 源URL | [http://ir.sia.cn/handle/173321/29929]  |
| 专题 | 沈阳自动化研究所_其他 |
| 通讯作者 | Zuo, Yinlong |
| 作者单位 | 1.Faculty of Robot Science and Engineering, Northeastern University, ShenYang, 110000, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, ShenYang, 110000, China |
| 推荐引用方式 GB/T 7714 | Zuo, Yinlong,Wang JT,Song JL. Application of YOLO Object Detection Network in Weld Surface Defect Detection[C]. 见:. Jiaxing, China. July 27-31, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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