img

QQ群聊

img

官方微信

高级检索

黄金科学技术 ›› 2021, Vol. 29 ›› Issue (1): 35-42.doi: 10.11872/j.issn.1005-2518.2021.01.162

• 智慧矿山专栏 • 上一篇    下一篇

地下铲运机自主铲装技术现状及发展趋势

姜丹(),王李管()   

  1. 中南大学资源与安全工程学院,湖南 长沙 410083
  • 收稿日期:2020-09-11 修回日期:2020-10-23 出版日期:2021-02-28 发布日期:2021-03-22
  • 通讯作者: 王李管 E-mail:1273801185@qq.com;liguan_wang@163.com
  • 作者简介:姜丹(1994-),女,四川资阳人,硕士研究生,从事矿山设备智能化研究工作。1273801185@qq.com
  • 基金资助:
    国家重点研发计划项目“深部集约化开采生产过程智能管控技术”(2017YFC0602905)

Present Situation and Development Trend of Self-loading Technology for Underground Load-Haul-Dump

Dan JIANG(),Liguan WANG()   

  1. School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China
  • Received:2020-09-11 Revised:2020-10-23 Online:2021-02-28 Published:2021-03-22
  • Contact: Liguan WANG E-mail:1273801185@qq.com;liguan_wang@163.com

摘要:

为提高地下铲运机铲装效率及作业精度,实现铲运机全自动作业,梳理了国内外地下铲运机自主铲装技术的相关理论技术和研究方法,并从环境感知与建模、铲斗轨迹控制和自动称重3个方面对铲装过程的研究成果进行了归纳总结。研究结果表明:当前环境感知与建模技术难以同时满足速度和精度的要求,存在铲斗轨迹控制难度大以及自动称重技术研究不全面等问题。研究多传感器信息融合技术,人工智能技术,以及适用于地下的通信网络是实现铲运机自主铲装的前提,也是未来开展该领域研究的重要方向。

关键词: 地下铲运机, 自主铲装, 感知建模, 轨迹控制, 称重系统, 人工智能

Abstract:

With the depletion of resources in open-pit mines,metal mines are gradually turning to deep mining. As the main equipment for loading and transporting ores in underground metal mines,the working environment of LHD(Load-Haul-Dump) is further deteriorated.The problems of harmful gases (CO,H2S,NH4,etc.),vibration,high stress and high temperature seriously affect people’s health.In order to protect the life health and personal safety of operators,improve the efficiency of mine operation and increase the economic benefits of mine,the intelligent mining technology of metal mine has been developed rapidly.The research on the automation of LHD has been carried out for more than 30 years,but the commercial system which has not fully realized the automatic loading can not be put into use.Because the shoveling is a dynamic and non-linear process,it is difficult to predict the change,which is the difficulty to realize the autonomous loading of LHD.In order to realize the full-automatic operation of LHD,this paper systematically studied the status quo and development trend of autonomous shoveling and loading of underground LHD,comprehensively summarized the three aspects of environmental perception and modeling,bucket trajectory control and automatic weighing,and analyzed the research status and shortcomings of its key technologies.The research results show that the environmental perception and modeling in the process of shoveling is mainly to establish the three-dimensional model of ore heap,and single type of sensor has shortcomings.Comprehensive use of the advantages of each sensor,information complementary and optimal combination can be realized.The interaction process between bucket and ore has the characteristics of dynamic change and non-linear,and the bucket trajectory control based on force is suitable for uniform medium,so it is difficult to apply in actual production.Reinforcement learning is widely used in the field of automatic control,through self-learning and adaptive environment to complete the operation task.The automatic weighing system can measure the effective load of the bucket and adjust the state of the ore in the bucket to prevent the ore from falling.There is a big gap in the research on the automatic weighing system at home and abroad.Compared with foreign countries,the automatic weighing technology in China is relatively backward,at the same time,the automatic weighing technology is mostly used in the ground loader,less in the underground.At present,there is also a big gap between China and foreign countries in the research of self loading technology of underground scraper.Strengthening cooperation in related fields and carrying out field test of LHD are the key points to promote the development of LHD in China.

Key words: underground LHD, automatic loading, perceptual modeling, trajectory control, weighing system, artificial intelligence

中图分类号: 

  • TD52

图1

铲运机自主铲装过程"

表1

各种传感器的比较"

传感器类型实现原理优点缺点
视觉摄像机根据光照构建物体深度图解析度高、视场广,价格低,算法丰富,具有通用性、精度高受光照影响,硬件投入大,不能实时建模
三维激光扫描仪根据分析时间推断仪器到矿堆的距离受光线的影响小,测量范围广,响应快,精度高,体积小价格高昂,数据处理复杂,单一位置信息无法识别物体
超声波测距仪根据飞行时间推断仪器到矿堆的距离受光线的影响小,价格低,体积小,可用于恶劣环境数据采集慢,解析度低,范围窄

表2

2种铲斗轨迹控制方法的优缺点比较"

方法实现方式优点缺点
基于力反馈的铲斗轨迹控制通过传感器参数调节铲斗运动实时反映铲斗受力情况适用均匀介质,复杂交互不适用
基于学习的铲斗轨迹控制通过训练相关参数,自动调节铲斗铲装自适应调节铲斗运动需要大量数据,应用范围窄
Ali D,Frimpong S,2020.Artificial intelligence,machine learning and process automation:Existing knowledge frontier and way forward for mining sector[J].Artificial Intelligence Review, 53(8):6025-6042.
Anthony Stentz J B S S,1999.A robotic excavator for autonomous truck loading[J].Autonomous Robots,7(2):175-186.
Chen Meng,Wang Liguan,Jia Mingtao,al et,2013.An overview of autonomous navigation techniques and development trend for underground LHD[J].China Safety Science Journal,23(3):130-134.
Dadhich S,Bodin U,Andersson U,2016a.Key challenges in automation of earth-moving machines[J].Automation in Construction,68:212-222.
Dadhich S,Bodin U,Sandin F,al et,2016b. Machine learning approach to automatic bucket loading[C]//Proceedings of 24th Mediterranean Conference on Control and Automation (MED).New York:Institute of Electrical and Electronics Engineers (IEEE):1260-1265.
Dobson A A,Marshall J A,Larsson J,2017.Admittance control for robotic loading:Design and experiments with a 1-Tonne loader and a 14-Tonne load-haul-dump machine[J].Journal of Field Robotics,34(1):123-150.
Eger T,Salmoni A,Whissell R,2004.Factors influencing load-haul-dump operator line of sight in underground mining[J].Applied Ergonomics,35(2):93-103.
Gao Mengxiong,2010a.The development of technology on underground loader and underground automobile automation(two)[J].Modern Mining,26(1):5-11.
Gao Mengxiong,2010b.The development of technology on underground loader and underground automobile automation(three)[J].Modern Mining,26(2):5-10.
Gu Desheng,2004.The development tendency of mining science and technology of underground metal mine[J].Gold,(1):18-22.
Guo Xin,Zhan Kai,Gu Hongshu,al et,2015.Theoretical research of dynamic weighing system of underground LHD[J].Nonferrous Metals(Mining Section),67(4):75-79.
Gustafson A,2011.Automation of load haul dump machines[R].Lulea:University of Lulea.
Hemami A F H,2005.Simulation study of a control procedure for automated loading of bulk media[C]//Proceedings of the 22nd International Symposium on Automation and Robotics in Construction ISARC.Ferrara:International Association for Automation and Robotics in Construction (IAARC). DOI: 10.22260/ISARC2005/0080
doi: 10.22260/ISARC2005/0080
Hemami A F H,2009.An overview of autonomous loading of bulk material[C]//Proceedings of the 26th International Symposium on Automation and Robotics in Construction.Austin TX:International Association for Automation and Robotics in Construction (IAARC):405-411.
Heshan A.Fernando J A M H,Larsson A J,2018.Towards controlling bucket fill factor in robotic excavation by learning admittance control setpoints[C]//Hutter,M.,Siegwart,R.,eds. Field and Service Robotics:Results of the 11Th International Conference.Cham, Switzerland: Springer International Publishing:35-48.
Lever P J A,2001.An automated digging control for a wheel loader[J].Robotica, 19(5):497-511.
Lever P J A,Wang F,1995.Intelligent excavator control system for lunar mining system[J].Journal of Aerospace Engineering,8(1):16-24.
Lever P J A,Wang F,Chen D,1994.A fuzzy control system for an automated mining excavator[C]//Proceedings of the 1994 IEEE International Conference on Robotics and Automation.New York:Institute of Electrical and Electronics Engineers (IEEE),29(3):3284-3289.
Li Hengtong,Guo Xin,Li Jianguo,al et,2015.Study on stratic automatic weighting of underground LHD[J].Mining Research and Development,35(11):85-88.
Li Jianguo,2016.Research on Automouous Control of Driving and Dumping for Underground Load-Haul-Dump[D].Beijing:University of Science and Technology Beijing.
Li Jun,2007.Study on Key Technique of Light Source in Machine Vision[D].Tianjin:Tianjin University of Technology.
Li Zhongxue,Li Cuiping,Li Shuangyue,2007.Frontiers in personless mining and avenues of their advancement in China[J].Strategic Study of CAE,(11):16-20.
Liu Hongfa,Wu Fei,2015.Design and implementation of the scraper automatic measuring system in multi-metal mine[J].Nonferrous Metals(Mining Section),67(4):80-81.
Ma Liguang,2005.The Research of Terrestrial Laser Scanning Technology[D].Wuhan:Wuhan University.
Mäkelä H,2001.Overview of LHD navigation without artificial beacons[J].Robotics and Autonomous Systems,36(1):21-35.
Marshall J A,Murphy P F,Daneshmend L K,2008.Toward autonomous excavation of fragmented rock:Full-scale experiments[J].IEEE Transactions on Automation Science and Engineering,5(3):562-566.
McKinnon C, Marshall J A,2014.Automatic identification of large fragments in a pile of broken rock using a time-of-flight camera[J].IEEE Transactions on Automation Science & Engineering,11(3):935-942.
Mikhirev P A,1983.Theory of the working cycle of automated rock-loading machines[J].Soviet Mining Science,6(19):515-522.
Petty M K,Billingsley J,Tran-Cong T,1997.Autonomous LHD loading[C]//Proceedings Fourth Annual Conference on Mechatronics and Machine Vision in Practice.New York: IEEE:219-224.
Quan Long,Li Yunhua,Fan Rujun,al et,2020.Research status and development trend of intelligent excavators [J].Journal of Mechanical Engineering,56(13):165-178.
Shi X,Lever P J A,Wang F Y,1996a.Experimental robotic excavation with fuzzy logic and neural networks[C]//Proceeding of IEEE International Conference on Robotics and Automation,Minneapolis.New York:IEEE:957-962.
Shi X,Lever P J A,Wang F Y,1996b.Fuzzy behavior integration and action fusion for robotic excavation[J].IEEE Transactions on Industrial Electronics,43(3):395-402.
Whitehorn M,2001.Stereo vision in LHD automation[J].IEEE Transactions on Industry Applictions,29(1):21-29.
Wu Di,2019.Positioning Technology of LHD Based on Stereo Visusal Odometry[D].Beijing:University of Science and Technology Beijing.
Wu Lixin,Wang Yunjia,Ding Enjie,al et,2012.Thirdly study on digital mine:Serve for mine safety and intellimine with support from Io T[J].Journal of China Coal Society,37(3):357-365.
Yang Qingping,Zhao Xingkuan,Wu Guomin,al et,2016.Automatic ore drawing technology of scraper and its application prospect[J].Mining Technology,16(6):21-25.
Yang Zhongjiong,2007.Simulation Research on Virtual Prototype Modeling And Dynamic Characteristics of Multi-Systems of Underground Load-Haul-Dump Vehicle[D].Changsha:Central South University.
Yin Chaozhong,Hu Tianyou,2009.Stydy on the optimal track of automatic shoveling of underground LHD[J].Metal Mine,(3):146-148.
Zhang Lifeng,Wang Rui,Ren Huajun,al et,2015.Mechanical analysis of scraper weighing system based on oil pressure measurement[J].Shandong Industrial Technology,(22):36.
陈盟,王李管,贾明涛,等,2013.地下铲运机自主导航研究现状及发展趋势[J].中国安全科学学报,23(3):130-134.
高梦熊,2010a.浅谈地下装载机、地下汽车自动化技术的发展(二)[J].现代矿业,26(1):5-11.
高梦熊,2010b.浅谈地下装载机、地下汽车自动化技术的发展(三)[J].现代矿业,26(2):5-10.
古德生,2004.地下金属矿采矿科学技术的发展趋势[J].黄金,(1):18-22.
郭鑫,战凯,顾洪枢,等,2015.地下铲运机动态称重系统的理论研究[J].有色金属(矿山部分),67(4):75-79.
李恒通,郭鑫,李建国,等,2015.地下铲运机静态自动称重技术研究[J].矿业研究与开发,35(11):85-88.
李建国,2016.地下铲运机自主行驶及卸载的控制研究[D].北京:北京科技大学.
李俊,2007.机器视觉照明光源关键技术研究[D].天津:天津理工大学.
李仲学,李翠平,刘双跃,2007.金属矿床地下自动开采的前沿技术及其发展途径[J].中国工程科学,(11):16-20.
刘宏发,吴飞,2015.多金属井下铲运机自动计量系统的设计与实现[J].有色金属(矿山部分),67(4):80-81.
马立广,2005.地面三维激光扫描测量技术研究[D].武汉:武汉大学.
权龙,李运华,范茹军,等,2020.智能化挖掘机的研究现状与发展趋势[J].机械工程学报,56(13):165-178.
吴荻,2019.基于立体视觉里程计的地下铲运机定位技术研究[D].北京:北京科技大学.
吴立新,汪云甲,丁恩杰,等,2012.三论数字矿山——借力物联网保障矿山安全与智能采矿[J].煤炭学报,37(3):357-365.
杨清平,赵兴宽,吴国珉,等,2016.铲运机自动化出矿技术及其应用前景[J].采矿技术,16(6):21-25.
杨忠炯,2007.地下铲运机多体系统虚拟样机建模及系统动态特性仿真研究[D].长沙:中南大学.
尹朝忠,胡天友,2009.地下铲运机自动铲取最优轨迹的研究[J].金属矿山,(3):146-148.
张丽峰,王锐,任华军,等,2015.基于油压测量的铲运机称重系统的力学分析[J].山东工业技术,(22):36.
[1] 刘永春,王李管,吴家希. 基于LQR-QPSO的地下铲运机控制参数优化研究[J]. 黄金科学技术, 2021, 29(1): 25-34.
[2] 毕林,李亚龙,郭昭宏. 基于深度卷积神经网络的卡车装载矿石量估计研究[J]. 黄金科学技术, 2019, 27(1): 112-120.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 王康林,汪模辉,蒋金龙. 难处理金矿石的细菌氧化预处理研究现状[J]. J4, 2001, 9(1): 19 -24 .
[2] 应汉龙,刘秉光. 胶东邓格庄金矿床围岩蚀变地球化学研究[J]. J4, 1995, 3(1): 39 -44 .
[3] 李建甘. 河台金矿床成矿地质规律研究[J]. J4, 2002, 10(2): 16 -22 .
[4] 龚朝阳, 江明阳. 广东河台金矿床成因分析与找矿方向[J]. J4, 2007, 15(4): 32 -35 .
[5] 孙虎,宋贵斌. 内蒙古虎拉林金矿平巷施工工艺探讨[J]. J4, 2007, 15(6): 38 -42 .
[6] 肖敬飞. 炭浆法处理河台金矿原矿石的工艺与实践[J]. J4, 2009, 17(3): 64 -67 .
[7] 路耀祖. 龙特锑金矿点地质特征及其找矿前景[J]. J4, 2008, 16(3): 13 -16 .
[8] 王忠军, 王永成, 姜维明, 胡世利, 刘金鹏. 降低金矿石回采边界品位分析与应用[J]. J4, 2007, 15(4): 54 -57 .
[9] 张中华, 张军艳. 几种过滤设备的特点及其效果[J]. J4, 2005, 13(1-2): 80 -83 .
[10] 黄俊,吴家富,鲁如魁 ,夏立元. 内蒙古兵图金矿成因探讨及找矿方向[J]. J4, 2010, 18(4): 1 -5 .