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井工煤矿运输系统智能化技术现状及发展趋势

陈晓晶

陈晓晶. 井工煤矿运输系统智能化技术现状及发展趋势[J]. 工矿自动化,2022,48(6):6-14, 35.  doi: 10.13272/j.issn.1671-251x.17933
引用本文: 陈晓晶. 井工煤矿运输系统智能化技术现状及发展趋势[J]. 工矿自动化,2022,48(6):6-14, 35.  doi: 10.13272/j.issn.1671-251x.17933
CHEN Xiaojing. Current status and development trend of intelligent technology of underground coal mine transportation system[J]. Journal of Mine Automation,2022,48(6):6-14, 35.  doi: 10.13272/j.issn.1671-251x.17933
Citation: CHEN Xiaojing. Current status and development trend of intelligent technology of underground coal mine transportation system[J]. Journal of Mine Automation,2022,48(6):6-14, 35.  doi: 10.13272/j.issn.1671-251x.17933

井工煤矿运输系统智能化技术现状及发展趋势

doi: 10.13272/j.issn.1671-251x.17933
基金项目: 天地科技股份有限公司科技创新创业资金专项项目(2021-TD-ZD004)。
详细信息
    作者简介:

    陈晓晶(1981—),男,江苏如东人,副研究员,主要研究方向为煤矿工业控制、物联网、智能化技术,E-mail:chxjme@163.com

  • 中图分类号: TD634/64

Current status and development trend of intelligent technology of underground coal mine transportation system

  • 摘要: 井工煤矿运输系统按运输对象不同可分为主运输系统和辅助运输系统。阐述了我国井工煤矿主运输系统和辅助运输系统底层装备和系统智能化技术现状,从顶层规划和标准体系、单机智能化等方面分析了主运输系统和辅助运输系统智能化技术存在的问题。重点介绍了3种主运输系统智能化关键技术,包括基于全数字化的FCS(现场总线控制系统)分布式带式输送机通信控制技术、基于机器音视觉的多传感融合增强型带式输送机保护技术、煤流线协同经济运行控制技术,以及2种辅助运输系统智能化关键技术,包括基于工业互联网架构的煤矿井下辅助运输管控一体化技术、煤矿井下车联网及无人驾驶技术。结合《煤矿智能化建设指南(2021年版)》对智能主煤流运输系统和智能辅助运输系统的要求,从近期和中远期阐述了井工煤矿主运输系统和辅助运输系统智能化发展趋势及目标。提出现阶段我国井工煤矿主运输系统应重点研究基于机器音视觉多传感融合的带式输送机增强型保护和检测技术、智能巡检机器人技术等,辅助运输系统应重点研究精细化闭环管控和高级辅助驾驶技术。

     

  • 图  1  基于全数字化的FCS分布式带式输送机通信控制架构

    Figure  1.  Distributed communication control structure of belt conveyor based on full digital fieldbus control system

    图  2  带式输送机多机互联和区域控制

    Figure  2.  Multi-machine interconnection and zone control of belt conveyor

    图  3  基于机器音视觉的多传感融合增强型带式输送机保护装置

    Figure  3.  Enhanced protection devices for belt conveyor based on multi-sensor fusion of machine audio-vision

    图  4  主运煤流协同控制系统界面

    Figure  4.  Coordinate control system interface of main coal flow transportion

    图  5  基于工业互联网架构的煤矿井下辅助运输管控一体化技术架构

    Figure  5.  Management and control integration technology structure of underground coal mine auxiliary transportation based on industrial Internet

    图  6  煤矿井下车联网及无人驾驶技术架构

    Figure  6.  Vehicle-to-everything and unmanned driving technology structure in underground coal mine

    图  7  全本安型智能机车保护控制装置

    Figure  7.  Full intrinsic safety type intelligent locomotive protection and control devices

  • [1] 王国法. 煤矿智能化最新技术进展与问题探讨[J]. 煤炭科学技术,2022,50(1):1-27.

    WANG Guofa. New technological progress of coal mine intelligence and its problems[J]. Coal Science and Technology,2022,50(1):1-27.
    [2] 王国法,庞义辉,刘峰,等. 智能化煤矿分类、分级评价指标体系[J]. 煤炭科学技术,2020,48(3):1-13.

    WANG Guofa,PANG Yihui,LIU Feng,et al. Specification and classification grading evaluation index system for intelligent coal mine[J]. Coal Science and Technology,2020,48(3):1-13.
    [3] 王国法,刘峰,庞义辉,等. 煤矿智能化−煤炭工业高质量发展的核心技术支撑[J]. 煤炭学报,2019,44(2):349-357.

    WANG Guofa,LIU Feng,PANG Yihui,et al. Coal mine intellectualization:the core technology of high quality development[J]. Journal of China Coal Society,2019,44(2):349-357.
    [4] 张世龙,张民波,朱仁豪,等. 近5年我国煤矿事故特征分析及防治对策[J]. 煤炭与化工,2021,44(8):101-106,109.

    ZHANG Shilong,ZHANG Minbo,ZHU Renhao,et al. Analysis of the characteristics of China's mine accidents in the past five years and countermeasures for prevention and control[J]. Coal and Chemical Industry,2021,44(8):101-106,109.
    [5] 马小平,杨雪苗,胡延军,等. 人工智能技术在矿山智能化建设中的应用初探[J]. 工矿自动化,2020,46(5):8-14.

    MA Xiaoping,YANG Xuemiao,HU Yanjun,et al. Preliminary study on application of artificial intelligence technology in mine intelligent construction[J]. Industry and Mine Automation,2020,46(5):8-14.
    [6] 王国法,赵国瑞,任怀伟. 智慧煤矿与智能化开采关键核心技术分析[J]. 煤炭学报,2019,44(1):34-41.

    WANG Guofa,ZHAO Guorui,REN Huaiwei. Analysis on key technologies of intelligent coal mine and intelligent mining[J]. Journal of China Coal Society,2019,44(1):34-41.
    [7] 丁震,赵永峰,尤文顺,等. 国家能源集团煤矿智能化建设路径研究[J]. 中国煤炭,2020,46(10):35-39. doi: 10.3969/j.issn.1006-530X.2020.10.007

    DING Zhen,ZHAO Yongfeng,YOU Wenshun,et al. Research on coal mine intelligent construction path of China Energy[J]. China Coal,2020,46(10):35-39. doi: 10.3969/j.issn.1006-530X.2020.10.007
    [8] 毛清华,毛金根,马宏伟,等. 矿用带式输送机智能监测系统研究[J]. 工矿自动化,2020,46(6):48-52,58.

    MAO Qinghua,MAO Jingen,MA Hongwei,et al. Research on intelligent monitoring system of mine-used belt conveyor[J]. Industry and Mine Automation,2020,46(6):48-52,58.
    [9] 赵远,吉庆,王腾. 煤矿智能无轨辅助运输技术现状与展望[J]. 煤炭科学技术,2021,49(12):209-216.

    ZHAO Yuan,JI Qing,WANG Teng. Current status and prospects of intelligent trackless auxiliary transportation technology in coal mines[J]. Coal Science and Technology,2021,49(12):209-216.
    [10] 王森良. 煤矿井下单轨吊机车辅助运输系统分析[J]. 矿业装备,2022(1):238-239. doi: 10.3969/j.issn.2095-1418.2022.01.112

    WANG Senliang. Analysis on auxiliary transport system of monorail crane locomotive in coal mine underground[J]. Mining Equipment,2022(1):238-239. doi: 10.3969/j.issn.2095-1418.2022.01.112
    [11] 宋连喜,刘波. 煤矿主运输智能集中控制系统设计[J]. 工矿自动化,2021,47(增刊1):58-63.

    SONG Lianxi,LIU Bo. Design of intelligent centralized control system for coal mine main transportation[J]. Industry and Mine Automation,2021,47(S1):58-63.
    [12] 杜京义,陈瑞,郝乐,等. 煤矿带式输送机异物检测[J]. 工矿自动化,2021,47(8):77-83.

    DU Jingyi,CHEN Rui,HAO Le,et al. Coal mine belt conveyor foreign object detection[J]. Industry and Mine Automation,2021,47(8):77-83.
    [13] 高强,高小强,任文清,等. 主煤流运输无人化智能视频管控系统[J]. 工矿自动化,2021,47(增刊2):60-61,102.

    GAO Qiang,GAO Xiaoqiang,REN Wenqing,et al. Unmanned intelligent video control system for main coal flow transportation[J]. Industry and Mine Automation,2021,47(S2):60-61,102.
    [14] 徐辉,刘丽静,沈科,等. 基于多道线性激光的带式输送机纵向撕裂检测[J]. 工矿自动化,2021,47(7):37-44.

    XU Hui,LIU Lijing,SHEN Ke,et al. Longitudinal tear detection of belt conveyor based on multi linear lasers[J]. Industry and Mine Automation,2021,47(7):37-44.
    [15] 周宇杰,徐善永,黄友锐,等. 基于改进YOLOv4的输送带损伤检测方法[J]. 工矿自动化,2021,47(11):61-65.

    ZHOU Yujie,XU Shanyong,HUANG Yourui,et al. Conveyor belt damage detection method based on improved YOLOv4[J]. Industry and Mine Automation,2021,47(11):61-65.
    [16] 蒋伟,吴高镇. 煤矿主运输煤流线信息支撑系统设计[J]. 工矿自动化,2018,44(10):1-5.

    JIANG Wei,WU Gaozhen. Design of information support system of coal flow line of coal mine main transportation[J]. Industry and Mine Automation,2018,44(10):1-5.
    [17] 李继来. 煤矿井下主运输煤流线协同控制研究[J]. 工矿自动化,2017,43(11):27-30.

    LI Jilai. Research on coordinate control of underground main coal transport route[J]. Industry and Mine Automation,2017,43(11):27-30.
    [18] 高彬,丁恩杰,董飞,等. 基于矿山物联网的井下物资管理系统设计[J]. 工矿自动化,2018,44(1):99-103.

    GAO Bin,DING Enjie,DONG Fei,et al. Design of underground material management system based on mine Internet of things[J]. Industry and Mine Automation,2018,44(1):99-103.
    [19] 陈杨阳,霍振龙,刘智伟,等. 我国煤矿运输机器人发展趋势及关键技术[J]. 煤炭科学技术,2020,48(7):233-242.

    CHEN Yangyang,HUO Zhenlong,LIU Zhiwei,et al. Development trend and key technology of coal mine transportation robot in China[J]. Coal Science and Technology,2020,48(7):233-242.
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出版历程
  • 收稿日期:  2022-04-17
  • 修回日期:  2022-05-09
  • 网络出版日期:  2022-06-28

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