基于改进YOLOv5算法的选矿摇床矿带分离点目标检测识别研究  

Recognition on ore zone separation points target detection and identification in mineral processing shaking table based on improved YOLOv5 algorithm

作　　者：刘惠中[1,2] 芮作为 朱合钧 彭志龙 LIU Huizhong;RUI Zuowei;ZHU Hejun;PENG Zhilong(School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi,China;Jiangxi Province Engineering Research Center for Mechanical and Electrical of Mining and Metallurgy,Ganzhou 341000,Jiangxi,China)

机构地区：[1]江西理工大学机电工程学院,江西赣州341000 [2]江西省矿冶机电工程技术研究中心,江西赣州341000

出　　处：《有色金属科学与工程》2025年第1期115-124,共10页Nonferrous Metals Science and Engineering

基　　金：江西省重点研发计划资助项目(20212BBE53026)。

摘　　要：摇床受到多个参数条件的影响,包括给矿量、给矿浓度、给矿品位以及给矿粒度等,床面上矿带的位置、颜色、宽度会随之发生相应的变化,为了保证精矿的品位,工人需要及时调节精矿截取位置以保证精矿品位的稳定。由于每个操作工的经验、技术不一样,容易造成生产指标的波动。为了减轻操作工人的劳动强度,提高选矿摇床矿物分选的自动化水平,本文提出了一种改进的YOLOv5目标检测算法,并对摇床精矿带和中矿带的分界点(矿带分离点)及标识点信息进行了成功提取。与YOLOv5、SSD、Faster-RCNN等其他算法对比,改进的YOLOv5算法的检测效果最好,精度最高,平均精度达98.3%。The operation of shaking tables in mineral processing is influenced by multiple parameters,including feed rate,feed concentration,feed grade,and feed particle size,which cause variations in the position,color,and width of the ore bands on the table surface.To ensure the quality of the concentrate,it's necessary for workers to timely adjust the position where the concentrate is collected,maintaining the stability of the concentrate grade.Varying experience and skills of operators often lead to the fluctuations in production indicators.To reduce the labor intensity of operators and enhance the level of automation in mineral sorting with shaking tables,this paper introduces an improved YOLOv5 target detection algorithm,which successfully extracts the boundary points(ore band separation points)and marker information of both the concentrate band and the middling band on the shaking table.Compared with other algorithms such as YOLOv5,SSD,and Faster-RCNN,the improved YOLOv5 algorithm demonstrates the best detection performance with the highest precision,achieving an average precision of 98.3%.

关 键 词：选矿摇床 YOLOv5 目标检测 自适应截取 

分 类 号：TD922[矿业工程—选矿]