| 基于YOLOv5和DeepSORT的金刚石锯丝磨损监测 |
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| 引用本文： | 袁俊涛,赵礼刚,秦齐,王天旭,刘志强. 基于YOLOv5和DeepSORT的金刚石锯丝磨损监测[J]. 金刚石与磨料磨具工程, 2023, 43(1): 96-101. DOI: 10.13394/j.cnki.jgszz.2022.0065 |
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| 作者姓名： | 袁俊涛 赵礼刚 秦齐 王天旭 刘志强 |
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| 作者单位： | 1.江苏科技大学 机械工程学院, 江苏 镇江 2120032.江苏科技大学, 江苏省船海机械装备先进制造重点实验室, 江苏 镇江 212003 |
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| 摘 要： | 为提高金刚石线锯切割的效率和质量，满足实时监测锯丝磨损的需求，提出一种基于改进的YOLOv5检测算法，在YOLOv5的基础上融合坐标注意力机制和BiFPN模块，使检测精确度、召回率、平均精度均值分别提高1.7%、3.7%、3.2%，能够有效检测不同磨损程度的磨粒；再连接DeepSORT多目标跟踪算法，设置虚拟检测线，统计不同磨损程度的磨粒数量，进而监测金刚石锯丝的磨损情况。
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| 关 键 词： | 金刚石锯丝 目标检测 YOLOv5 DeepSORT |
| 收稿时间： | 2022-05-05 |
Wear monitoring of diamond saw wire based on YOLOv5 and DeepSORT |
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| YUAN Juntao,ZHAO Ligang,QIN Qi,WANG Tianxu,LIU Zhiqiang. Wear monitoring of diamond saw wire based on YOLOv5 and DeepSORT[J]. Diamond & Abrasives Engineering, 2023, 43(1): 96-101. DOI: 10.13394/j.cnki.jgszz.2022.0065 |
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| Authors: | YUAN Juntao ZHAO Ligang QIN Qi WANG Tianxu LIU Zhiqiang |
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| Affiliation: | 1.School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China2.Jiangsu Provincial Key Laboratory of Advanced Manufacturing for Marine Mechanical Equipment, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China |
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| Abstract: | In order to improve the efficiency and quality of diamond wire saw cutting and meet the demand of real-time monitoring of saw wire wear, a detection algorithm based on improved YOLOv5 was proposed. The algorithm combined coordinate attention mechanism and BiFPN module on the basis of YOLOv5. The detection accuracy, recall rate and average accuracy were increased by 1.7%, 3.7% and 3.2% respectively. Abrasive particles with different wear degrees can be effectively detected. Besides, the DeepSORT multi-target tracking algorithm was connected to set up a virtual detection line, count the number of abrasive particles with different wear degrees, and monitor the wear of diamond saw wire. |
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