Research progress on coal rock recognition technology based on electromagnetic waves
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摘要: 将电磁波应用于煤岩识别中,可有效提高煤岩界面分辨能力。结合煤岩界面模型,阐述了运用电磁波技术进行煤岩识别的原理;介绍了γ射线法、雷达探测法、太赫兹信号法、电子共振法、X射线法和红外热成像法6种具体的煤岩识别方法,分析了各方法的原理,对各方法的优缺点及煤矿井下适用性进行了对比,并结合实际工业应用分析了各方法的研究现状。γ射线法在探测距离上具有显著优势,但存在放射性问题,基本被淘汰;雷达探测法具有识别准确的优点,但由于其信号衰减严重,探测距离短,目前一般应用于薄煤层测厚;太赫兹信号法探测距离短,只有在井下环境组成稳定时才能应用;电子共振法信号衰减严重,探测距离较短且难度较大,所以目前矿井基本摒弃;X射线法穿透性强,成像较清晰,但危害性极大;红外热成像法中,主动红外激励法需耗费大量时间对煤岩进行激励,且在处于高瓦斯的矿井环境中,存在极大的安全隐患;截割闪温法虽耗时较短,但对于截齿多、排布复杂的情况很难实现有效的煤岩识别。指出电磁波回波信息决定着电磁波煤岩识别的准确性,后续应对其进行深层次挖掘。Abstract: Applying electromagnetic waves to coal rock recognition can effectively improve the resolution capability of coal rock interfaces. Based on the coal rock interface model, the principle of using electromagnetic wave technology for coal rock recognition is explained. The paper introduces six methods for coal rock recognition, including γ–ray method, radar detection method, Terahertz signal method, electron resonance method, X-ray method, and infrared thermal imaging method. The principles of each method are analyzed, and the advantages and disadvantages of each method are compared as well as their applicability in coal mines underground. The research status of each method is analyzed in combination with practical industrial applications. The γ–ray method has significant advantages in detection distance, but it has radiation problems. It is basically eliminated. The radar detection method has the advantage of accurate recognition, but due to its severe signal attenuation and short detection distance, it is currently generally used for thickness measurement in thin coal seams. The Terahertz signal method has a short detection distance and can only be applied when the composition of the underground environment is stable. The electronic resonance method has severe signal attenuation, short detection distance, and high difficulty. It is currently basically abandoned in mines. The X-ray method has strong penetration and clear imaging, but it poses great harm. In the infrared thermal imaging method, the active infrared excitation method requires a lot of time to excite coal and rock, and there are significant safety hazards in high gas mine environments. Although the cutting flash temperature method takes a short time, it is difficult to achieve effective coal rock recognition for situations with multiple cutting teeth and complex layout. It is pointed out that the accuracy of electromagnetic wave coal rock recognition is determined by the echo information of electromagnetic waves, and further in-depth exploration should be carried out.
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表 1 6种基于电磁波的煤岩识别方法综合对比
Table 1. Comprehensive comparison of six coal and rock recognition methods based on electromagnetic wave
识别方法 优点 缺点 煤矿井下适用性 γ射线法 探测距离较远 对放射性元素含量有要求 煤层放射性达标 雷达探测法 识别准确 信号衰减严重,探测距离较短 介质电性差异明显 太赫兹信号法 透射非极性介质多,可同时获取煤岩的多个光学参数 探测距离较短,对环境要求较高 矿井环境组成稳定 电子共振法 介质共振吸收现象明显 信号衰减严重,探测距离较短 目前矿井基本摒弃 X射线法 穿透性强,成像较清晰 探测距离较短,危害性较大 一般用于煤矸分选 红外热成像法 对井下复杂环境适用性强 耗时长 矿井瓦斯含量低,截齿少且排布较简单 -
[1] 杨元. 我国煤矿井下复杂地质条件下钻探技术与装备进展[J]. 内蒙古煤炭经济,2021(24):195-197.YANG Yuan. Progress of drilling technology and equipment under complex geological conditions in coal mines in China[J]. Inner Mongolia Coal Economy,2021(24):195-197. [2] 石智军,刘建林,李泉新. 我国煤矿区钻进技术装备发展与应用[J]. 煤炭科学技术,2018,46(4):1-6.SHI Zhijun,LIU Jianlin,LI Quanxin. Development and application of drilling technique and equipment in coal mining area of China[J]. Coal Science and Technology,2018,46(4):1-6. [3] 林柏泉,李庆钊,杨威,等. 基于千米钻机的“三软”煤层瓦斯治理技术及应用[J]. 煤炭学报,2011,36(12):1968-1973.LIN Baiquan,LI Qingzhao,YANG Wei,et al. Gas control technology and applications for the three-soft coal seam based on VLD-1000 drilling systems[J]. Journal of China Coal Society,2011,36(12):1968-1973. [4] 张世阔,曹思华. 复杂地质条件下矿井安全高效开采地质保障技术[J]. 煤矿安全,2010,41(4):70-73.ZHANG Shikuo,CAO Sihua. The technology of mine safety and efficient mining geology assurance under complicated geological conditions[J]. Safety in Coal Mines,2010,41(4):70-73. [5] 张强,张润鑫,刘峻铭,等. 煤矿智能化开采煤岩识别技术综述[J]. 煤炭科学技术,2022,50(2):1-26.ZHANG Qiang,ZHANG Runxin,LIU Junming,et al. Review on coal and rock identification technology for intelligent mining in coal mines[J]. Coal Science and Technology,2022,50(2):1-26. [6] 许会,陈艳玲. 微波成像技术及其算法综述[J]. 无损检测,2012,34(10):67-71,82.XU Hui,CHEN Yanling. Overview of the technology and algorithm of microwave imaging[J]. Nondestructive Testing,2012,34(10):67-71,82. [7] 李海英,杨汝良. 超宽带雷达的发展、现状及应用[J]. 遥感技术与应用,2001(3):178-183.LI Haiying,YANG Ruliang. Development,state-of-the-art and applications of ultra-wideband radar[J]. Remote Sensing Technology and Application,2001(3):178-183. [8] 开滦煤炭科学研究所. 低能γ射线测灰仪[J]. 煤炭科学技术,1977,5(7):26-28.Kailuan Coal Science Research Institute. Low energy gamma ray ash analyzer[J]. Coal Science and Technology,1977,5(7):26-28. [9] 纪钢,李冬辉,吴学胜. 天然γ射线穿过煤的规律性研究[J]. 煤炭学报,1994,19(1):65-70.JI Gang,LI Donghui,WU Xuesheng. Study of rules of natural γ-rays passing through coal seam[J]. Journal of China Coal Society,1994,19(1):65-70. [10] 韩成石,董长双,周西军,等. 煤和矸石γ–射线分选系统的研究[J]. 山西矿业学院学报,1997,15(2):45-49.HAN Chengshi,DONG Changshuang,ZHOU Xijun,et al. Research on a system of separating coal from stone by γ-ray[J]. Shanxi Mining Institute Learned Journal,1997,15(2):45-49. [11] 王增才,孟惠荣. 支架顶梁对γ射线方法测量顶煤厚度影响研究[J]. 中国矿业大学学报,2002,31(3):323-326.WANG Zengcai,MENG Huirong. Influence of canopy of hydraulic support upon measurting thickness of coal seam by natural gamma ray[J]. Journal of China University of Mining & Technology,2002,31(3):323-326. [12] 张宁波. 综放开采煤矸自然射线辐射规律及识别研究[D]. 徐州:中国矿业大学,2015.ZHANG Ningbo. Detection and radiation law of natural gamma ray from coal and roof-rock in the fully mechanized top coal caving mining[D]. Xuzhou:China University of Mining and Technology,2015. [13] 赵明鑫. 综放煤矸放落的环境特征及自动识别的影响因素研究[D]. 徐州:中国矿业大学,2020.ZHAO Mingxin. Study on drawing environmental characteristics and influence factors of coal-gangue automatic identification in fully mechanized top coal caving ming[D]. Xuzhou:China University of Mining and Technology,2020. [14] 杨增福,张海军,蒲平武. 基于自然γ射线探测原理的煤层厚度测量精度优化方法研究[J]. 煤炭科学技术,2021,49(增刊2):287-291.YANG Zengfu,ZHANG Haijun,PU Pingwu. Optimization method of coal seam thickness measurement accuracy based on natural γ-ray detection principle[J]. Coal Science and Technology,2021,49(S2):287-291. [15] ELLERBRUCH D A,ADAMS J W. Microwave measurement of coal layer thickness[R/OL]. [2023-05-12]. https://nvlpubs.nist.gov/nistpubs/Legacy/IR/nbsir74-387.pdf. [16] ELLERBRUCH D A,BELSHER D R. Electromagnetic technique of measuring coal layer thickness[J]. IEEE Transactions on Geoscience Electronics,1978,16(2):126-133. doi: 10.1109/TGE.1978.294575 [17] DANIELS D J. Short pulse radar for stratified lossy dielectric layer measurement[J]. IEE Proceedings F(Communications,Radar and Signal Processing),1980,127(5):384-388. [18] CHUFO R L,JOHNSON W J. A radar coal thickness sensor[C]. IEEE Industry Applications Society Annual Meeting,Dearborn,1991:1182-1191. [19] MOWREY G L,GANOE C,MONAGHAN W D. A radar-based highwall rib-thickness monitoring system[J]. Fuel and Energy Abstracts,1997,38(3):194. [20] RALSTON J C,HAINSWORTH D W,MCPHEE R J. Application of ground penetrating radar for coal thickness measurement[C]. IEEE Region 10 Annual Conference,Brisbane,1997:835-838. [21] STRANGE A D,CHANDRAN V,RALSTON J C. Coal seam thickness estimation using GPR and higher order statistics - the near-surface case[C]. The Eighth International Symposium on Signal Processing and Its Applications,Sydney,2005:855-858. [22] 王昕,丁恩杰,胡克想,等. 煤岩散射特性对探地雷达探测煤岩界面的影响[J]. 中国矿业大学学报,2016,45(1):34-41.WANG Xin,DING Enjie,HU Kexiang,et al. Effects of coal-rock scattering characteristics on the GPR detection of coal-rock interface[J]. Journal of China University of Mining & Technology,2016,45(1):34-41. [23] 刘帅,赵文生,高思伟. 超宽带探地雷达煤层厚度探测试验研究[J]. 煤炭科学技术,2019,47(8):207-212.LIU Shuai,ZHAO Wensheng,GAO Siwei. Experimental study on coal seam thickness measurement of ultra-wide band ground penetrating radar[J]. Coal Science and Technology,2019,47(8):207-212. [24] 许献磊,王一丹,朱鹏桥,等. 基于高频雷达波的煤岩层位识别与追踪方法研究[J]. 煤炭科学技术,2022,50(7):50-58.XU Xianlei,WANG Yidan,ZHU Pengqiao,et al. Research on coal and rock horizon identification and tracking method based on high frequency radar waves[J]. Coal Science and Technology,2022,50(7):50-58. [25] 杨成全,孟田华,卢玉和. 云冈石窟石质、降尘样品的太赫兹光谱分析[J]. 山西大同大学学报(自然科学版),2011,27(2):17-19.YANG Chengquan,MENG Tianhua,LU Yuhe. Research on Terahertz spectrum of the Yungang Grotto samples[J]. Journal of Shanxi Datong University(Natural Science Edition),2011,27(2):17-19. [26] 宝日玛,赵昆,赵卉. 岩石的太赫兹光谱特性研究[J]. 现代科学仪器,2013(1):115-117,121.BAO Rima,ZHAO Kun,ZHAO Hui. Optical property of rock in Terahertz region[J]. Modern Scientific Instruments,2013(1):115-117,121. [27] 许长虹,滕学明,赵卉,等. 煤炭中氢含量与挥发分的太赫兹时域光谱研究[J]. 现代科学仪器,2013(4):228-230.XU Changhong,TENG Xueming,ZHAO Hui,et al. Analysis of hydrogen and volatile matter content in coal maceral using time-resolved Terahertz spectroscopy[J]. Modern Scientific Instruments,2013(4):228-230. [28] 王昕,苗曙光,丁恩杰. 煤岩介质在太赫兹频段的介电特性研究[J]. 中国矿业大学学报,2016,45(4):739-746.WANG Xin,MIAO Shuguang,DING Enjie. Study of dielectric property of coal and rock medium in Terahertz domain[J]. Journal of China University of Mining & Technology,2016,45(4):739-746. [29] 王昕,胡克想,俞啸,等. 基于太赫兹时域光谱技术的煤岩界面识别[J]. 工矿自动化,2017,43(1):29-34.WANG Xin,HU Kexiang,YU Xiao,et al. Coal-rock interface recognition based on Terahertz time-domain spectroscopy[J]. Industry and Mine Automation,2017,43(1):29-34. [30] 虞婧. 基于太赫兹光谱技术的煤岩在线识别方法研究[D]. 徐州:中国矿业大学,2021.YU Jing. Study on online identification method of coal and rock based on Terahertz spectroscopy[D]. Xuzhou:China University of Mining and Technology,2021. [31] 苗曙光,邵丹,刘忠育,等. 基于太赫兹时域光谱技术的煤岩识别方法研究[J]. 光谱学与光谱分析,2022,42(6):1755-1760.MIAO Shuguang,SHAO Dan,LIU Zhongyu,et al. Study on coal-rock identification method based on Terahertz time-domain spectroscopy[J]. Spectroscopy and Spectral Analysis,2022,42(6):1755-1760. [32] 苗曙光. 基于GPR与ESR的煤岩性状识别方法研究[D]. 徐州:中国矿业大学,2019.MIAO Shuguang. Study of coal-rock characteristics identification method based on GPR and ESR[D]. Xuzhou:China University of Mining and Technology,2019. [33] 曲星武,王金城. 煤的X射线分析[J]. 煤田地质与勘探,1980,8(2):33-40.QU Xingwu,WANG Jincheng. X-ray analysis of coal[J]. Coal Geology & Exploration,1980,8(2):33-40. [34] 李春山. X射线荧光岩屑识别技术研究[D]. 西安:西北大学,2010.LI Chunshan. Research on X-ray fluorescence cuttings identification technology[D]. Xi'an:Northwest University,2010. [35] 杨慧刚,乔志敏. 基于X射线和机器视觉的煤与矸石分选系统设计[J]. 工矿自动化,2017,43(3):85-89.YANG Huigang,QIAO Zhimin. Design of separation system of coal and gangue based on X-ray and machine vision[J]. Industry and Mine Automation,2017,43(3):85-89. [36] 耿秀云. 基于X光图像处理的煤矸石自动分选系统的研究[D]. 沈阳:东北大学,2014.GENG Xiuyun. Research on automatic sorting system of coal and rock based on X-ray image processing[D]. Shenyang:Northeastern University,2017. [37] 司垒,谭超,朱嘉皓,等. 基于X射线图像和激光点云的煤矸识别方法[J]. 仪器仪表学报,2022,43(9):193-205.SI Lei,TAN Chao,ZHU Jiahao,et al. A coal-gangue recognition method based on X-ray image and laser point cloud[J]. Chinese Journal of Scientific Instrument,2022,43(9):193-205. [38] 桂林电子科技大学. 一种基于主动激励红外热成像的煤岩界面识别装置:CN201721418045.6[P]. 2017-10-31.Guilin University of Electronic Technology. A coal-rock interface recognition device based on active excitation infrared thermal imaging is presented:CN201721418045.6[P]. 2017-10-31. [39] 张强,孙绍安,张坤,等. 基于主动红外激励的煤岩界面识别[J]. 煤炭学报,2020,45(9):3363-3370.ZHANG Qiang,SUN Shao'an,ZHANG Kun,et al. Coal and rock interface identification based on active infrared excitation[J]. Journal of China Coal Society,2020,45(9):3363-3370. [40] HARGRAVE C O,REID D C,HAINSWORTH D W,et al. Mining methods and apparatus:US 2009/0212216A1[P]. 2009-08-27. [41] RALSTON J C,STRANGE A D. Thermal infrared-based seam tracking for intelligent longwall shearer horizon control[C]. 12th Coal Operators' Conference,2012:78-85. [42] 张强,王海舰,王兆,等. 基于红外热像检测的截齿煤岩截割特性与闪温分析[J]. 传感技术学报,2016,29(5):686-692.ZHANG Qiang,WANG Haijian,WANG Zhao,et al. Analysis of coal-rock's cutting characteristics and flash temperature for peak based on infrared thermal image testing[J]. Chinese Journal of Sensors and Actuators,2016,29(5):686-692. [43] 张强,王海舰,郭桐,等. 基于截齿截割红外热像的采煤机煤岩界面识别研究[J]. 煤炭科学技术,2017,45(5):22-27.ZHANG Qiang,WANG Haijian,GUO Tong,et al. Study on coal-rock interface recognition of coal shearer based on cutting infrared thermal image of picks[J]. Coal Science and Technology,2017,45(5):22-27. [44] 刘建伟. KJH–D型防爆探地雷达在新景矿掘进巷道的应用[J]. 山东煤炭科技,2021,39(12):182-185.LIU Jianwei. Application of KJH-D explosion-proof ground penetrating radar in driving roadway of Xinjing Coal Mine[J]. Shandong Coal Science and Technology,2021,39(12):182-185. [45] 池津维. 王家岭煤矿12309工作面顶煤破碎特征及运移规律研究[J]. 能源与环保,2023,45(2):281-284.CHI Jinwei. Research on top coal fragmentation characteristics and movement law of 12309 working face in Wangjialing Coal Mine[J]. China Energy and Environmental Protection,2023,45(2):281-284. [46] 徐坤,李欣睿,陈忍忍. 地质雷达在煤矿采空区的探测应用研究[J]. 地质装备,2022,23(6):25-27,37.XU Kun,LI Xinrui,CHEN Renren. Research on the detection application of ground penetration radar in coal mine goaf[J]. Equipment for Geotechnical Engineering,2022,23(6):25-27,37.