Citation: | YAN Bijuan, WANG Kaimin, GUO Pengcheng, et al. Research on coal gangue detection in coal preparation plant based on YOLOv5s-FSW model[J]. Journal of Mine Automation,2024,50(5):36-43, 66. doi: 10.13272/j.issn.1671-251x.2023100090 |
[1] |
金智新,曹孟涛,王宏伟. “中等收入”与新“双控”背景下煤炭行业转型发展新机遇[J]. 煤炭科学技术,2023,51(1):45-58.
JIN Zhixin,CAO Mengtao,WANG Hongwei. New opportunities for coal industry transformation and development under the background of the level of a moderately developed country and a new "dual control" system[J]. Coal Science and Technology,2023,51(1):45-58.
|
[2] |
李君清,李寅琪. 煤炭产业经济走势及煤炭企业对策研究[J]. 中国煤炭,2023,49(3):16-22. doi: 10.3969/j.issn.1006-530X.2023.03.003
LI Junqing,LI Yinqi. Study on the development trend of coal industry economy and countermeasures of coal enterprises[J]. China Coal,2023,49(3):16-22. doi: 10.3969/j.issn.1006-530X.2023.03.003
|
[3] |
周宏春. 新型能源体系破解能源保供与降碳双重压力研究与探讨[J]. 中国煤炭,2023,49(5):1-10. doi: 10.3969/j.issn.1006-530X.2023.05.001
ZHOU Hongchun. Research and discussion on breaking the dual pressure of energy supply guarantee and carbon reduction by the new energy system[J]. China Coal,2023,49(5):1-10. doi: 10.3969/j.issn.1006-530X.2023.05.001
|
[4] |
朱吉茂,孙宝东,张军,等. “双碳”目标下我国煤炭资源开发布局研究[J]. 中国煤炭,2023,49(1):44-50. doi: 10.3969/j.issn.1006-530X.2023.01.006
ZHU Jimao,SUN Baodong,ZHANG Jun,et al. Research on China's coal resources development layout under the goals of carbon peak and carbon neutrality[J]. China Coal,2023,49(1):44-50. doi: 10.3969/j.issn.1006-530X.2023.01.006
|
[5] |
唐珏,王俊. “双碳”目标下煤炭发展及对策建议[J]. 中国矿业,2023,32(9):22-31. doi: 10.12075/j.issn.1004-4051.20230483
TANG Jue,WANG Jun. Coal development and countermeasures under the carbon peaking and carbon neutrality goals[J]. China Mining Magazine,2023,32(9):22-31. doi: 10.12075/j.issn.1004-4051.20230483
|
[6] |
郭静,李磊,李志明. 干法选煤技术创新进展及其节能节水降污效果分析[J]. 中国煤炭,2022,48(5):68-75. doi: 10.3969/j.issn.1006-530X.2022.05.012
GUO Jing,LI Lei,LI Zhiming. Innovation progress of dry coal preparation technology and analysis of its effect of energy saving,water saving and pollution reduction[J]. China Coal,2022,48(5):68-75. doi: 10.3969/j.issn.1006-530X.2022.05.012
|
[7] |
刘志杰. 重介洗煤技术在选煤厂的应用[J]. 能源与节能,2023(7):136-138. doi: 10.3969/j.issn.2095-0802.2023.07.036
LIU Zhijie. Application of heavy medium coal washing technology in coal preparation plant[J]. Energy and Energy Conservation,2023(7):136-138. doi: 10.3969/j.issn.2095-0802.2023.07.036
|
[8] |
ZHANG Ningbo,LIU Changyou. Radiation characteristics of natural gamma-ray from coal and gangue for recognition in top coal caving[J]. Scientific Reports,2018,8(1):190. doi: 10.1038/s41598-017-18625-y
|
[9] |
韩子彬,王丽宏,申志刚,等. 基于X射线分选方法在选煤厂中的应用[J]. 煤炭科学技术,2022,50(增刊1):327-332.
HAN Zibin,WANG Lihong,SHEN Zhigang,et al. Application of X-ray separation method in coal preparation plant[J]. Coal Science and Technology,2022,50(S1):327-332.
|
[10] |
蔡秀凡,谢金辰. YOLOv4煤矸石检测方法研究[J]. 煤炭工程,2022,54(8):157-162.
CAI Xiufan,XIE Jinchen. YOLOv4-based detection method of coal and gangue[J]. Coal Engineering,2022,54(8):157-162.
|
[11] |
来文豪,周孟然,胡锋,等. 基于多光谱成像和改进YOLOv4的煤矸石检测[J]. 光学学报,2020,40(24):72-80.
LAI Wenhao,ZHOU Mengran,HU Feng,et al. Coal gangue detection based on multi-spectral imaging and improved YOLOv4[J]. Acta Optica Sinica,2020,40(24):72-80.
|
[12] |
高如新,常嘉浩,杜亚博,等. 基于改进YOLOv5s的煤矸石目标检测算法[J]. 电子测量技术,2023,46(13):95-101.
GAO Ruxin,CHANG Jiahao,DU Yabo,et al. Coal gangue target detection algorithm based on improved YOLOv5s[J]. Electronic Measurement Technology,2023,46(13):95-101.
|
[13] |
郑道能. 一种改进的tiny YOLOv3煤矸石快速识别模型[J]. 工矿自动化,2023,49(4):113-119.
ZHENG Daoneng. An improved tiny YOLOv3 rapid recognition model for coal-gangue[J]. Journal of Mine Automation,2023,49(4):113-119.
|
[14] |
陈彪,卢兆林,代伟,等. 基于轻量化HPG−YOLOX−S模型的煤矸石图像精准识别[J]. 工矿自动化,2022,48(11):33-38.
CHEN Biao,LU Zhaolin,DAI Wei,et al. Accurate recognition of coal-gangue image based on lightweight HPG-YOLOX-S model[J]. Journal of Mine Automation,2022,48(11):33-38.
|
[15] |
桂方俊,李尧. 基于CBA−YOLO模型的煤矸石检测[J]. 工矿自动化,2022,48(6):128-133.
GUI Fangjun,LI Yao. Coal gangue detection based on CBA-YOLO model[J]. Journal of Mine Automation,2022,48(6):128-133.
|
[16] |
张释如,黄综浏,张袁浩,等. 基于改进YOLOv5的煤矸识别研究[J]. 工矿自动化,2022,48(11):39-44.
ZHANG Shiru,HUANG Zongliu,ZHANG Yuanhao,et al. Coal and gangue recognition research based on improved YOLOv5[J]. Journal of Mine Automation,2022,48(11):39-44.
|
[17] |
张磊,王浩盛,雷伟强,等. 基于YOLOv5s−SDE的带式输送机煤矸目标检测[J]. 工矿自动化,2023,49(4):106-112.
ZHANG Lei,WANG Haosheng,LEI Weiqiang,et al. Coal gangue target detection of belt conveyor based on YOLOv5s-SDE[J]. Journal of Mine Automation,2023,49(4):106-112.
|
[18] |
REDMON J,FARHADI A. YOLOv3:an incremental improvement[C]. IEEE Conference on Computer Vision and Pattern Recognition,Salt Lake City,2018:89-95.
|
[19] |
芦碧波,周允,李小军,等. 融合注意力机制的YOLOv5轻量化煤矿井下人员检测算法[J]. 煤炭技术,2023,42(10):200-203.
LU Bibo,ZHOU Yun,LI Xiaojun,et al. YOLOv5 lightweight coal mine underground personnel detection algorithm base on attention mechanism[J]. Coal Technology,2023,42(10):200-203.
|
[20] |
CHEN Jierun,KAO Shiuhong,HE Hao,et al. Run,don't walk:chasing higher FLOPS for faster neural networks[C]. IEEE/CVF Conference on Computer Vision and Pattern Recognition,Vancouver,2023:12021-12031.
|
[21] |
HU Jie,SHEN Li,SUN Gang. Squeeze-and-excitation networks[C]. IEEE Conference on Computer Vision and Pattern Recognition,Salt Lake City,2018:7132-7141.
|
[22] |
WOO S,PARK J C,LEE J Y,et al. Cbam:convolutional block attention module[C]. European Conference on Computer Vision,Munich,2018:3-19.
|
[23] |
柏罗,张宏立,王聪. 基于高效注意力和上下文感知的目标跟踪算法[J]. 北京航空航天大学学报,2022,48(7):1222-1232.
BAI Luo,ZHANG Hongli,WANG Cong. Target tracking algorithm based on efficient attention and context awareness[J]. Journal of Beijing University of Aeronautics and Astronautics,2022,48(7):1222-1232.
|
[24] |
YANG Lingxiao,ZHANG Ruyuan,LI Lida,et al. Simam:a simple,parameter-free attention module for convolutional neural networks[C]. International Conference on Machine Learning,New York,2021:11863-11874.
|
[25] |
JIANG Borui,LUO Ruixuan,MAO Jiayuan,et al. Acquisition of localization confidence for accurate object detection[C]. European Conference on Computer Vision,Munich,2018:816-832.
|
[26] |
ZHENG Zhaohui,WANG Ping,REN Dongwei,et al. Enhancing geometric factors in model learning and inference for object detection and instance segmentation[J]. IEEE Transactions on Cybernetics,2021,52(8):8574-8586.
|
[27] |
TONG Zanjia,CHEN Yuhang,XU Zewei,et al. Wise−IoU:bounding box regression loss with dynamic focusing mechanism[J]. Computer Science,2023. DOI: 10.48550/arXiv.2301.10051.
|