CUI Yao,WU Jinghong,YE Zhuang,et al. Research and application of key technology of intelligent coal caving in high gas fully-mechanized top coal caving face[J]. Coal Science and Technology,2023,51(10):252−265
. DOI: 10.13199/j.cnki.cst.2022-1407Citation: |
CUI Yao,WU Jinghong,YE Zhuang,et al. Research and application of key technology of intelligent coal caving in high gas fully-mechanized top coal caving face[J]. Coal Science and Technology,2023,51(10):252−265 . DOI: 10.13199/j.cnki.cst.2022-1407 |
At present, intelligent coal caving in high gas fully mechanized top coal caving face is facing many problems, mainly including poor recognition accuracy of coal gangue, incomplete control research on coal flow and gas concentration, cumbersome design and development of follow-up process, and slow response of control system.In order to solve these problems, this paper developed a cloud side collaborative intelligent coal caving control system based on 5G communication.The system includes 5G network, cloud server, edge processor, terminal execution equipment, etc.It has a high data transmission speed, control response speed and data processing capability.Based on the analysis of fully mechanized coal caving process parameters and intelligent coal caving process flow, elaborates the four key technologies of intelligent coal caving the coal gangue identification technology, big block coal identification and coal flow load balance technology, gas safety linkage control technology, and digital twin technology of coal caving following machine.The application test was carried out in Baode 81309 fully mechanized top coal caving face.After the intelligent fully mechanized top coal caving technology was adopted, the top coal recovery rate increased from 86% to 93%, the coal gangue rate decreased from 21% to 15%, the total production efficiency increased by 10%, and the number of coal caving operators decreased from 3 to 4 to 1 to 2.The cloud edge collaborative intelligent coal caving control system based on 5G communication developed in this paper and its key technologies can also be extended to other fully mechanized coal caving faces, which is of great value for reducing personnel and increasing efficiency and safe and efficient mining of coal mines.
[1] |
CREEDY D, LIJIE W, XINQUAN Z, et al. Transforming China's coal mines: A case history of the Shuangliu Mine[C]//Natural Resources Forum. Oxford, UK: Blackwell Publishing Ltd, 2006, 30(1): 15-26.
|
[2] |
滕吉文,乔勇虎,宋鹏汉. 我国煤炭需求、探查潜力与高效利用分析[J]. 地球物理学报,2016,59(12):4633−4653. doi: 10.6038/cjg20161224
TENG Jiwen,QIAO Yonghu,SONG Penghan. Analysis of exploration, potential reserves and high efficient utilization of coal in China[J]. Chinese Journal of Geophysics,2016,59(12):4633−4653. doi: 10.6038/cjg20161224
|
[3] |
宋选民,朱德福,王仲伦,等. 我国煤矿综放开采40年: 理论与技术装备研究进展[J]. 煤炭科学技术,2021,49(3):1−29.
SONG Xuanmin,ZHU Defu,WANG Zhonglun,et al. Advances on longwall full-mechanized top-coal caving mining technology in China during past 40 years: theory, equipment and approach[J]. Coal Science and Technology,2021,49(3):1−29.
|
[4] |
SONG Z,KONIETZKY H,HERBST M. Drawing mechanism of fractured top coal in longwall top coal caving[J]. International journal of rock mechanics and mining sciences,2020,130:104329. doi: 10.1016/j.ijrmms.2020.104329
|
[5] |
ZHANG N,LIU C,YANG P. Flow of top coal and roof rock and loss of top coal in fully mechanized top coal caving mining of extra thick coal seams[J]. Arabian Journal of Geosciences,2016,9(6):1−9.
|
[6] |
ALEHOSSEIN H,POULSEN B A. Stress analysis of longwall top coal caving[J]. International Journal of Rock Mechanics and Mining Sciences,2010,47(1):30−41. doi: 10.1016/j.ijrmms.2009.07.004
|
[7] |
YANG S,ZHANG J,CHEN Y,et al. Effect of upward angle on the drawing mechanism in longwall top-coal caving mining[J]. International Journal of Rock Mechanics and Mining Sciences,2016,85:92−101. doi: 10.1016/j.ijrmms.2016.03.004
|
[8] |
张守祥,张学亮,刘 帅,等. 智能化放顶煤开采的精确放煤控制技术[J]. 煤炭学报,2020,45(6):2008−2020. doi: 10.13225/j.cnki.jccs.zn20.0329
ZHANG Shouxiang,ZHANG Xueliang,LIU Shuai,et al. Intelligent precise control technology of fully mechanized top coal caving face[J]. Journal of China Coal Society,2020,45(6):2008−2020. doi: 10.13225/j.cnki.jccs.zn20.0329
|
[9] |
赵亦辉,赵友军,周 展. 综采工作面采煤机智能化技术研究现状[J]. 工矿自动化,2022,48(2):11−18. doi: 10.13272/j.issn.1671-251x.2021090024
ZHAO Yihui,ZHAO Youjun,ZHOU Zhan. Research status of intelligent technology of shearer in fully mechanized working face[J]. Journal of Mine Automation,2022,48(2):11−18. doi: 10.13272/j.issn.1671-251x.2021090024
|
[10] |
胡亚辉,赵国瑞,吴群英. 面向煤矿智能化的5G关键技术研究[J]. 煤炭科学技术,2022,50(2):223−230. doi: 10.13199/j.cnki.cst.2020-1093
HU Yahui,ZHAO Guorui,WU Qunying. Research on 5G key technologies in intelligent coal mining[J]. Coal Science and Technology,2022,50(2):223−230. doi: 10.13199/j.cnki.cst.2020-1093
|
[11] |
邱 美. 5G时代的智慧矿山[J]. 支部建设,2021(2):22−24.
QIU Mei. Smart mine in 5G Era[J]. Branch Construction,2021(2):22−24.
|
[12] |
吴劲松. 麻地梁煤矿智慧矿山建设系统及其应用实践[J]. 中国煤炭,2021,47(S1):57−68. doi: 10.3969/j.issn.1006-530X.2021.z1.009
WU Jinsong. Intelligent mine construction systems amnd their application practices in Madiliang Coal Mine[J]. China Coal,2021,47(S1):57−68. doi: 10.3969/j.issn.1006-530X.2021.z1.009
|
[13] |
王家臣,潘卫东,张国英,等. 图像识别智能放煤技术原理与应用[J]. 煤炭学报,2022,47(1):87−101. doi: 10.13225/j.cnki.jccs.yg21.1530
WANG Jiachen,PAN Weidong,ZHANG Guoying,et al. Principles and applications of images-based recognition of withdrawn coal and intelligent control of draw opening in longwall top coal caving face[J]. Journal of China Coal Society,2022,47(1):87−101. doi: 10.13225/j.cnki.jccs.yg21.1530
|
[14] |
朱帝杰,陈忠辉. 综放开采顶煤采出率预测模型的构建与应用[J]. 煤炭学报,2019,44(9):2641−2649. doi: 10.13225/j.cnki.jccs.2018.1297
ZHU Dijie,CHEN Zhonghui. A model for top coal recovery ratio assessment and its application in longwall top coal caving[J]. Journal of China Coal Society,2019,44(9):2641−2649. doi: 10.13225/j.cnki.jccs.2018.1297
|
[15] |
许永祥,李申龙,王国法,等. 特厚坚硬煤层超大采高综放首采工作面智能化技术[J]. 煤炭科学技术,2020,48(7):186−194. doi: 10.13199/j.cnki.cst.2020.07.019
XU Yongxiang,LI Shenlong,WANG Guofa,et al. Intelligent technology of first-mining face of longwall top-coal caving with super large cutting height in extra-thick and hard coal seam[J]. Coal Science and Technology,2020,48(7):186−194. doi: 10.13199/j.cnki.cst.2020.07.019
|
[16] |
刘长友,张宁波,郭凤岐,等. 特厚煤层综放煤-矸-岩放落流动的时序规律及识别方法[J]. 煤炭学报,2022,47(1):137−151. doi: 10.13225/j.cnki.jccs.yg21.1896
LIU Changyou,ZHANG Ningbo,GUO Fengqi,et al. Sequential rules and identification method of coal-gangue-rock caving flow in fully mechanized top-coal-caving workface of extra thick coal seam[J]. Journal of China Coal Society,2022,47(1):137−151. doi: 10.13225/j.cnki.jccs.yg21.1896
|
[17] |
潘卫东,李新源,员明涛,等. 基于顶煤运移跟踪仪的自动化放煤技术原理及应用[J]. 煤炭学报,2020,45(S1):23−30. doi: 10.13225/j.cnki.jccs.ZN20.0273
PAN Weidong,LI Xinyuan,YUAN Mingtao,et al. Technology principle and field application of automatic coal drawing based on the top coal tracker[J]. Journal of China Coal Society,2020,45(S1):23−30. doi: 10.13225/j.cnki.jccs.ZN20.0273
|
[18] |
刘 闯,李化敏,周 英,等. 综放工作面多放煤口协同放煤方法[J]. 煤炭学报,2019,44(9):2632−2640. doi: 10.13225/j.cnki.jccs.2018.1278
LIU Chuang,LI Huamin,ZHOU Ying,et al. Method of synergetic multi-windows caving in longwall top coal caving working face[J]. Journal of China Coal Society,2019,44(9):2632−2640. doi: 10.13225/j.cnki.jccs.2018.1278
|
[19] |
王 伸,黄贞宇,李东印,等. 特厚煤层分组间隔放煤顶煤运移规律研究[J]. 煤炭科学技术,2021,49(9):17−24. doi: 10.13199/j.cnki.cst.2021.09.003
WANG Shen,HUANG Zhenyu,LI Dongyin,et al. Study of top-coal flow mechanism under interval and multi-grouping top-coal caving technology in extra thick coal seam[J]. Coal Science and Technology,2021,49(9):17−24. doi: 10.13199/j.cnki.cst.2021.09.003
|
[20] |
YANG L, Li L, WEI W. Optimization of caving technology in an extrathick seam with longwall top coal caving mining[J]. Advances in Materials Science and Engineering, 2021.
|
[21] |
WANG J,YANG S,WEI W,et al. Drawing mechanisms for top coal in longwall top coal caving (LTCC): a review of two decades of literature[J]. International Journal of Coal Science & Technology,2021,8(6):1171−1196.
|
[22] |
牛云鹏,张立亚,贺云龙. 智能大采高综采工作面视频分析系统的研究与应用[J]. 中国煤炭,2020,46(6):40−44. doi: 10.3969/j.issn.1006-530X.2020.06.008
NIU Yunpeng,ZHANG Liya,HE Yunlong. Research and application of video analysis system of intelligent fully mechanized working face with large mining height[J]. China Coal,2020,46(6):40−44. doi: 10.3969/j.issn.1006-530X.2020.06.008
|
[23] |
俎少杰,王 强,韩进军. 基于视觉煤流检测的矿井皮带机变频调速系统[J]. 机械管理开发,2022,37(3):239−241. doi: 10.16525/j.cnki.cn14-1134/th.2022.03.101
ZU Shaojie,WANG Qiang,HAN Jinjun. Variable frequency speed control system for mine belt machine based on visual coal flow detection[J]. Mechanical Management and Development,2022,37(3):239−241. doi: 10.16525/j.cnki.cn14-1134/th.2022.03.101
|
[24] |
夏蒙健,刘 洋. 煤流智能调速策略研究[J]. 工矿自动化,2022,48(S2):108−111.
XIA Mengjian,LIU Yang. Study on intelligent speed regulation strategy of coal flow[J]. Journal of Mine Automation,2022,48(S2):108−111.
|
[25] |
蒋卫良,王兴茹,刘 冰,等. 煤矿智能化连续运输系统关键技术研究[J]. 煤炭科学技术,2020,48(7):134−142. doi: 10.13199/j.cnki.cst.2020.07.013
JIANG Weiliang,WANG Xingru,LIU Bing,et al. Study on key technology of coal mine intelligent continuous transportation[J]. Coal Science and Technology,2020,48(7):134−142. doi: 10.13199/j.cnki.cst.2020.07.013
|
[26] |
张 飞. 寸草塔二矿31203综放工作面瓦斯来源及分布规律[J]. 陕西煤炭,2020,39(S2):26−30.
ZHANG Fei. Gas source and distribution law of fully mechanized caving face in Cuncaota No. 2 Mine[J]. Shaanxi Coal,2020,39(S2):26−30.
|
[27] |
王 沉,杨 帅,江成玉,等. 基于瓦斯浓度监测反馈的采煤机截割速度自适应调节技术[J]. 煤炭工程,2019,51(4):134−137.
WANG Chen,YANG Shuai,JIANG Chengyu,et al. Self-adaptive adjustment technology of shearer cutting speed based on monitoring feedback of methane concentration[J]. Coal Engineering,2019,51(4):134−137.
|
[28] |
布朋生. 高瓦斯煤矿综采工作面采煤机速度动态控制系统研究[J]. 自动化仪表,2020,41(7):69−71, 78. doi: 10.16086/j.cnki.issn1000-0380.2020010030
BU Pengsheng. Research on dynamic control system of shearer speed in fully mechanized face of high gas coal mine[J]. Process Automation Instrumentation,2020,41(7):69−71, 78. doi: 10.16086/j.cnki.issn1000-0380.2020010030
|
[29] |
卢东贵,屈世甲. 瓦斯浓度预测与采煤机控制关联方法的探讨[J]. 煤矿安全,2016,47(3):152−155. doi: 10.13347/j.cnki.mkaq.2016.03.042
LU Donggui,QU Shijia. Discussion on Gas Concentration Prediction Associated with Coal Cutter Control Methods[J]. Safety in Coal Mines,2016,47(3):152−155. doi: 10.13347/j.cnki.mkaq.2016.03.042
|
[30] |
顾义东. 5G技术在煤矿掘进工作面运输系统中的应用[J]. 工矿自动化,2022,48(6):64−68. doi: 10.13272/j.issn.1671-251x.17919
GU Yidong. Application of 5G technology in coal mine heading face transportation system[J]. Journal of Mine Automation,2022,48(6):64−68. doi: 10.13272/j.issn.1671-251x.17919
|
[31] |
杨 鑫,时晓厚,沈 云,等. 5G工业互联网的边缘计算技术架构与应用[J]. 电子技术应用,2019,45(12):25−28,33. doi: 10.16157/j.issn.0258-7998.191153
YANG Xin,SHI Xiaohou,SHEN Yun,et al. Edge computing applications and technical architecture of 5G industrial Internet[J]. Application of Electronic Technique,2019,45(12):25−28,33. doi: 10.16157/j.issn.0258-7998.191153
|
[32] |
李 艺,刘春平,武晓雪. 基于5G技术的智能矿山研究及应用[J]. 中国煤炭,2020,46(11):42−48. doi: 10.3969/j.issn.1006-530X.2020.11.006
LI Yi,LIU Chunping,WU Xiaoxue. Research and application of 5G technology in intelligent mine[J]. China Coal,2020,46(11):42−48. doi: 10.3969/j.issn.1006-530X.2020.11.006
|
[33] |
王雍昌. 特厚煤层综放开采放煤工艺参数研究[J]. 同煤科技,2020(4):8−11. doi: 10.19413/j.cnki.14-1117.2020.04.003
WANG Yongchang. Study on technical parameters of fully mechanized top coal caving mining in extra thick coal seam[J]. Datong Coal Science & Technology,2020(4):8−11. doi: 10.19413/j.cnki.14-1117.2020.04.003
|
[34] |
王晓飞. 厚煤层综采放顶煤开采工艺参数研究[J]. 煤炭工程,2018,50(9):56−58.
WANG Xiaofei. Study on technological parameters of fully mechanized top-coal caving mining in thick coal seam[J]. Coal Engineering,2018,50(9):56−58.
|
[35] |
邓维元,康天合. 特厚煤层综放开采放煤工艺优化研究[J]. 煤炭工程,2017,49(4):52−55. doi: 10.11799/ce201704017
DENG Weiyuan,KANG Tianhe. Coal drawing process optimization of full-mechanized top-coal caving in extra-thick coal seam[J]. Coal Engineering,2017,49(4):52−55. doi: 10.11799/ce201704017
|
[36] |
乔中栋,屈 英,杨国宏,等. 华亭煤矿综放工作面合理采高及放煤工艺分析[J]. 煤矿安全,2020,51(11):161−164. doi: 10.13347/j.cnki.mkaq.2020.11.034
QIAO Zhongdong,QU Ying,YANG Guohong,et al. Determination on reasonable mining height and top coal caving technology in Huating Coal Mine[J]. Safety in Coal Mines,2020,51(11):161−164. doi: 10.13347/j.cnki.mkaq.2020.11.034
|
[37] |
郭金刚,李化敏,王祖洸,等. 综采工作面智能化开采路径及关键技术[J]. 煤炭科学技术,2021,49(1):128−138. doi: 10.13199/j.cnki.cst.2021.01.007
GUO Jingang,LI Huamin,WANG Zuguang,et al. Path and key technologies of intelligent mining in fully-mechanized coal mining face[J]. Coal Science and Technology,2021,49(1):128−138. doi: 10.13199/j.cnki.cst.2021.01.007
|
[38] |
张学亮,刘 清,郎瑞峰,等. 厚煤层智能放煤工艺及精准控制关键技术研究[J]. 煤炭工程,2020,52(9):1−6.
ZHANG Xueliang,LIU Qing,LANG Ruifeng,et al. Intelligent coal drawing process and the key technologies of precise control for thick coal seam top-coal caving[J]. Coal Engineering,2020,52(9):1−6.
|
[39] |
曹现刚,李 莹,王 鹏,等. 煤矸石识别方法研究现状与展望[J]. 工矿自动化,2020,46(1):38−43. doi: 10.13272/j.issn.1671-251x.2019060005
CAO Xiangang,LI Ying,WANG Peng,et al. Research status of coal-gangue identification method and its prospect[J]. Journal of Mine Automation,2020,46(1):38−43. doi: 10.13272/j.issn.1671-251x.2019060005
|
[40] |
BESSINGER S L,NELSON M G. Remnant roof coal thickness measurement with passive gamma ray instruments in coal mines[J]. IEEE Transactions on Industry Applications,1993,29(3):562−565. doi: 10.1109/28.222427
|
[41] |
蒋 磊,马六章,杨克虎,等. 基于MFCC和FD-CNN卷积神经网络的综放工作面煤矸智能识别[J]. 煤炭学报,2020,45(S2):1109−1117. doi: 10.13225/j.cnki.jccs.2020.0738
JIANG Lei,MA Liuzhang,YANG Kehu,et al. Coal and gangue intelligent separation based on MFCC and FD-CNN convolutional neural network for top coal caving mining[J]. Journal of China Coal Society,2020,45(S2):1109−1117. doi: 10.13225/j.cnki.jccs.2020.0738
|
[42] |
JUNKAI X,ZENGCAI W,WANZHI Z,et al. Coal-rock interface recognition based on MFCC and neural network[J]. International Journal of Signal Processing, Image Processing and Pattern Recognition,2013,6(4):191−200.
|
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![]() | |
15. |
孙娈娈,王中华. 突出煤层区域预测瓦斯含量临界值研究. 山东煤炭科技. 2023(03): 110-112 .
![]() | |
16. |
何志刚,邢祥,王振刚,谷晓亮. 红岭煤矿工作面突出预测敏感指标测定及应用. 中国矿山工程. 2023(02): 53-58+69 .
![]() | |
17. |
徐耀松,白济宁,王雨虹,阎馨,王丹丹. 基于CEEMDAN-DA-GRU的瓦斯涌出量预测模型. 传感技术学报. 2023(03): 441-448 .
![]() | |
18. |
李延河. 地面井分区式瓦斯抽采技术体系及工程实践. 煤炭科学技术. 2023(03): 100-108 .
![]() | |
19. |
杨琪,于岩斌,崔文亭,高成伟,张鑫,申家龙. 单轴压缩下煤岩细观结构参数表征及演化规律. 煤炭科学技术. 2023(04): 88-95 .
![]() | |
20. |
郭鑫. 寺河煤矿东井3号煤层突出预测敏感性指标研究. 煤炭与化工. 2023(06): 114-119 .
![]() | |
21. |
夏治华,汪国良. 兴隆煤矿工作面突出预测敏感指标及临界值研究. 江西煤炭科技. 2023(03): 136-139 .
![]() | |
22. |
梁运培,郑梦浩,李全贵,毛树人,栗小雨,李建波,周俊江. 我国煤与瓦斯突出预测与预警研究现状. 煤炭学报. 2023(08): 2976-2994 .
![]() | |
23. |
郭武奎,靳鹏. 大水头煤矿一采区瓦斯压力临界值考察研究. 山西化工. 2023(10): 127-130 .
![]() | |
24. |
张天军,孟钰凯,庞明坤,张磊,武晋宇. 有效应力对孔周破裂煤体渗透率演化规律的影响. 煤炭科学技术. 2023(S1): 122-131 .
![]() | |
25. |
谢亚东,吴琪璇,李作泉,张建江,权继业. 采动应力与工作面突出指标相关性分析. 中国安全科学学报. 2023(S2): 96-99 .
![]() | |
26. |
唐巨鹏,任凌冉,潘一山,张昕. 高地应力条件煤与瓦斯突出模拟试验研究. 煤炭科学技术. 2022(02): 113-121 .
![]() | |
27. |
周礼杰,陈亮,程志恒,艾国,孔德中,王蕾,王宏冰,郭凯. 突出厚煤层沿空掘巷煤柱留设宽度优化研究. 煤炭科学技术. 2022(03): 92-101 .
![]() | |
28. |
吕情绪,肖剑儒,满洋. 低瓦斯煤层高强综放开采工作面合理长度确定. 煤矿安全. 2022(05): 188-193 .
![]() | |
29. |
成小雨,龚选平,尉瑞,高涵,赵刚. 考虑煤体粒度的落煤瓦斯涌出预测模型研究. 中国安全生产科学技术. 2022(07): 61-67 .
![]() | |
30. |
朱墨然,王麒翔,张庆华. 多源数据驱动的防突预警指标自适应技术研究. 煤炭科学技术. 2022(08): 75-81 .
![]() | |
31. |
郝建峰,梁冰,孙维吉,石占山,施永威,赵航. 煤与瓦斯的热流固耦合关系研究现状及展望. 采矿与安全工程学报. 2022(05): 1051-1060+1070 .
![]() | |
32. |
杨威. 东曲矿瓦斯突出敏感指标预测及临界值研究. 煤. 2022(11): 38-39+48 .
![]() | |
33. |
迟羽淳,邹永洺. 敏感指标预测煤层瓦斯异常涌出应用分析. 中国矿业. 2022(11): 117-122 .
![]() | |
34. |
王林杉. 河南省某矿二_1煤层突出预测敏感指标及临界值研究. 内蒙古煤炭经济. 2022(20): 5-8 .
![]() | |
35. |
周银波,李晓丽,李晗晟,王佳乐,毛淑星,王世杰. 煤体吸附变形对3种气体渗透率演化的影响. 煤矿安全. 2021(11): 16-21 .
![]() | |
36. |
单大阔. 瓦斯为突出主导因素的煤层突出预测敏感指标及临界值考察. 煤. 2021(12): 20-22+93 .
![]() | |
37. |
孙际宏,左安家,魏超,陈江龙. 煤层突出危险性预测敏感指标考察确定. 华北科技学院学报. 2021(05): 33-39 .
![]() |