机械工程 |
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基于改进YOLOv8s的鼓形滚子表面缺陷检测算法 |
王安静1( ),袁巨龙1,*( ),朱勇建2,陈聪1,吴金津1 |
1. 浙江工业大学 机械工程学院,浙江 杭州 310023 2. 宁波敏捷信息科技有限公司,浙江 慈溪 315300 |
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Drum roller surface defect detection algorithm based on improved YOLOv8s |
Anjing WANG1( ),Julong YUAN1,*( ),Yongjian ZHU2,Cong CHEN1,Jinjin WU1 |
1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China 2. Ningbo Agile Information Technology Limited Company, Cixi 315300, China |
引用本文:
王安静,袁巨龙,朱勇建,陈聪,吴金津. 基于改进YOLOv8s的鼓形滚子表面缺陷检测算法[J]. 浙江大学学报(工学版), 2024, 58(2): 370-380.
Anjing WANG,Julong YUAN,Yongjian ZHU,Cong CHEN,Jinjin WU. Drum roller surface defect detection algorithm based on improved YOLOv8s. Journal of ZheJiang University (Engineering Science), 2024, 58(2): 370-380.
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https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2024.02.015
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https://www.zjujournals.com/eng/CN/Y2024/V58/I2/370
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1 |
王姮, 卜燕, 张华, 等 基于分形维数的磁痕图像缺陷检测[J]. 计算机应用研究, 2015, 32 (2): 603- 605 WANG Heng, BU Yan, ZHANG Hua, et al Defect detection of magnetic trace image based on fractal dimension[J]. Application Research of Computers, 2015, 32 (2): 603- 605
doi: 10.3969/j.issn.1001-3695.2015.02.063
|
2 |
梁子千, 玄文博, 王婷, 等 基于二维阻抗特征的管道环焊缝缺陷涡流检测[J]. 仪器仪表学报, 2017, 38 (9): 2138- 2145 LIANG Ziqian, XUAN Wenbo, WANG Ting, et al Eddy current detection of pipe girth weld defects based on two-dimensional impedance characteristics[J]. Chinese Journal of Scientific Instrument, 2017, 38 (9): 2138- 2145
doi: 10.3969/j.issn.0254-3087.2017.09.006
|
3 |
陈振华, 郑志远, 卢超 不锈钢焊缝中超声传播特性及TOF检测方法研究[J]. 电子测量与仪器学报, 2017, 31 (7): 1129- 1136 CHEN Zhenhua, ZHENG Zhiyuan, LU Chao Study on ultrasonic propagation characteristics and TOFD detection method in stainless steel weld[J]. Journal of Electronic Measurement and Instrumentation, 2017, 31 (7): 1129- 1136
|
4 |
WANG J M, QIAO J P, GUO M C Research on bearing surface defect detection system based on machine vision[J]. Journal of Physics: Conference Series, 2022, 2290 (1): 012061
doi: 10.1088/1742-6596/2290/1/012061
|
5 |
LU M H, CHEN C L Detection and classification of bearing surface defects based on machine vision[J]. Applied Sciences, 2021, 11 (4): 1825
doi: 10.3390/app11041825
|
6 |
陈昊, 张奔, 黎明, 等 基于图像光流的轴承滚子表面缺陷检测[J]. 仪器仪表学报, 2018, 39 (6): 198- 206 CHEN Hao, ZHANG Ben, LI Ming, et al Bearing roller surface defect detection based on image optical flow[J]. Chinese Journal of Scientific Instrument, 2018, 39 (6): 198- 206
|
7 |
陈丹阳, 曹丽, 林一高, 等 轴承圆锥滚子外观缺陷检测研究[J]. 机电工程, 2015, 32 (8): 1084- 1087 CHEN Danyang, CAO Li, LIN Yigao, et al Study on appearance defect detection of bearing tapered roller[J]. Mechanical and Electrical Engineering, 2015, 32 (8): 1084- 1087
|
8 |
GIRSHICK R. Fast r-CNN [C]//2015 IEEE International Conference on Computer Vision. Santiago: IEEE, 2015: 1440-1448.
|
9 |
袁天乐, 袁巨龙, 朱勇建, 等 基于改进YOLOv5的推力球轴承表面缺陷检测算法[J]. 浙江大学学报: 工学版, 2022, 56 (12): 2349- 2357 YUAN Tianle, YUAN Julong, ZHU Yongjian, et al Surface defect detection algorithm for thrust ball bearing based on improved YOLOv5[J]. Journal of Zhejiang University: Engineering Science, 2022, 56 (12): 2349- 2357
|
10 |
曾耀, 高法钦 基于改进YOLOv5的电子元件表面缺陷检测算法[J]. 浙江大学学报: 工学版, 2023, 57 (3): 455- 465 ZENG Yao, GAO Faqin Surface defect detection algorithm for electronic components based on improved YOLOv5[J]. Journal of Zhejiang University: Engineering Science, 2023, 57 (3): 455- 465
|
11 |
TAN M, PANG R, LE Q V. Efficientdet: scalable and efficient object detection [C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Seattle: IEEE, 2020: 10781-10790.
|
12 |
CONG P C, FENG H, LV K F, et al MYOLO: a light weight fresh Shiitake mushroom detection model based on YOLOv3[J]. Agriculture, 2023, 13 (2): 392
doi: 10.3390/agriculture13020392
|
13 |
LIANG C, YAN Z G, REN M, et al Improved YOLOv5 infrared tank target detection method under ground background[J]. Scientific Reports, 2023, 13 (1): 6269
doi: 10.1038/s41598-023-33552-x
|
14 |
WANG C Y, BOCHKOVSKIY A, LIAO H Y M. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville: IEEE, 2023: 7464–7475.
|
15 |
WANG C Y, BOCHKOVSKIY A, LIAO H Y M. Scaled-yolov4: scaling cross stage partial network [C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. [S. l. ]: IEEE, 2021: 13029-13038.
|
16 |
GE Z, LIU S, WANG F, et al. Yolox: exceeding yolo series in 2021 [EB/OL]. [2023-05-17]. https://arxiv.org/pdf/2107.08430.pdf.
|
17 |
SUNKARA R, LUO T. No more strided convolutions or pooling: a new CNN building block for low-resolution images and small objects [C]//European Conference on Computer Vision. [S. l. ]: Springer, 2022: 19–23.
|
18 |
JIANG Y, TAN Z, WANG J, et al. GiraffeDet: a heavy-neck paradigm for object detection[EB/OL]. [2023-05-17]. https://arxiv.org/pdf/2202.04256.pdf.
|
19 |
LIU S, QI L, QIN H, et al. Path aggregation network for instance segmentation [C] //Proceedings of the IEEE Conference onComputer Vision and Pattern Recognition. Lake City: IEEE, 2018: 8759-8768.
|
20 |
TONG Z, CHEN Y, XU Z, et al. Wise-IoU: bounding box regression loss with dynamic focusing mechanism [EB/OL]. [2023-05-17]. https://arxiv.org/pdf/2301.10051.pdf.
|
21 |
LIU W, ANGUELOV D, ERHAN D, et al. SSD: singleshot multibox detector [EB/OL]. [2023-05-17]. https://arxiv.org/ pdf/1512.02325.pdf.
|
22 |
REDMON J, FARHADI A. YOLOv3: an incremental improvement [EB/OL]. [2023-05-17]. https://arxiv.org/pdf/1804.02767.pdf.
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