Abstract: By clarifying the problems constraining the development of drilling and blasting construction technology—including complex processes, outdated equipment, high labor demands, and information fragmentation—the foundation was laid for building a minimally manned or unmanned intelligent rock roadways(tunneling)excavation system. Based on this, a comprehensive review was conducted on the current development status of intelligent drilling and blasting technologies and equipment for rock roadways(tunneling). Firstly, the basic concept and essence of intelligent drilling and blasting were elaborated, defined as an integrated blasting technology that utilizes advanced technologies such as AI to achieve deep self-perception of information, intelligent self-optimized decision-making, and precise self-executed control. Subsequently, the research status of intelligent tunnel drilling and blasting technology was systematically summarized, with key advancements and shortcomings covered in: blasting materials, transparent geological technology, intelligent blasting parameter design, intelligent drilling and blasting construction technologies/equipment, precision blasting technology, and blasting quality management. Finally, future trends in intelligent drilling and blasting technology and equipment for rock roadways(tunneling)were outlined, with proposals for establishing a full life-cycle intelligent excavation system centered on digitalization, automation, and intelligence, aimed at achieving safe, efficient, and green underground engineering construction.
岳中文,刘化强,刘伟,金庆雨,陈佳瑶. 岩巷(隧道)智能化钻爆技术与装备研究现状及展望[J]. 隧道与地下工程灾害防治, 2025, 7(3): 1-20.
YUE Zhongwen, LIU Huaqiang, LIU Wei, JIN Qingyu, CHEN Jiayao. Research status and prospects of intelligent drilling and blasting technology and equipment for rock roadways(tunneling)Symbol`@@. Hazard Control in Tunnelling and Underground Engineering, 2025, 7(3): 1-20.
[1] 汪旭光, 吴春平, 陶刘群. 智能爆破[M]. 北京: 冶金工业出版社, 2020. [2] 吴春平, 汪旭光. 智能爆破的基本概念与研究内容[J]. 金属矿山, 2023(5): 59-63. WU Chunping, WANG Xuguang. Basic concepts and research contents about intelligent blasting[J]. Metal Mine, 2023(5): 59-63. [3] 王志坚, 童建军. 钻爆法隧道智能建造技术研究综述与展望[J]. 隧道建设(中英文), 2023, 43(4): 529-548. WANG Zhijian, TONG Jianjun. Overview and prospect of researches on intelligent engineering technologies for tunnels constructed by drilling-and-blasting method[J]. Tunnel Construction, 2023, 43(4): 529-548. [4] 许涛. 公路隧道光面爆破设计系统研究与开发[D]. 长春: 吉林大学, 2013. XU Tao. Research and development of the highway tunnel smooth blasting design system[D]. Changchun: Jilin University, 2013. [5] 刘大斌. 塑料导爆管的起爆、传爆及输出性能研究[D]. 南京: 南京理工大学, 2002. LIU Dabin. Study of the initiation, explosion transferring and output character performance of noneltube[D]. Nanjing: Nanjing University of Science and Technology, 2002. [6] 谭忠盛, 吴金刚. 我国隧道钻爆法施工技术回顾与展望[J]. 隧道建设(中英文), 2023, 43(6): 899-920. TAN Zhongsheng, WU Jingang. Review and prospects of drilling and blasting tunnel construction technology in China[J]. Tunnel Construction, 2023, 43(6): 899-920. [7] ZHANG X Y, YAN P, LU W B, et al. Frequency spectrum characteristics of blast-induced vibration with electronic detonators in ground blasting[J]. Journal of Building Engineering, 2023, 74: 106892. [8] LENG Z D, FAN Y, LU W B, et al. Failure mechanisms of electronic detonators subjected to high impact loading in rock drilling and blasting[J]. International Journal of Coal Science & Technology, 2025, 12(1): 10. [9] HOBBS H. Orica reports successful production trials of the WebGen[EB/OL].(2017-09-27)[2025-03-19]. https://www.globalminingreview.com/product-news/27092017/orica-reports-successful-production-trials-of-the- webgen [10] LEVISON W G. On the origin and sequences of the minerals of the Newark(Triassic)igneous rocks of new jersey[J]. Annals of the New York Academy of Sciences, 1909, 19(1): 121-134. [11] R. C. G. Nitroglycerine explosives[J]. Nature, 1929, 123(3088): 8-9. [12] 杨年华, 高菊茹. 在隧道爆破中机械化装填重铵油炸药的应用前景[J]. 现代隧道技术, 2000(2): 26-28. YANG Nianhua, GAO Juru. Prospects of mechanized loading of emulan explosives tunnel blasting[J]. Modern Tunnelling Technology, 2000(2):26-28. [13] 李术才, 刘斌, 孙怀凤, 等. 隧道施工超前地质预报研究现状及发展趋势[J]. 岩石力学与工程学报, 2014, 33(6): 1090-1113. LI Shucai, LIU Bin, SUN Huaifeng, et al. State of art and trends of advanced geological prediction in tunnel construction[J]. Chinese Journal of Rock Mechanics and Engineering, 2014, 33(6): 1090-1113. [14] PAN D D, XU Z H, LU X M, et al. 3D scene and geological modeling using integrated multi-source spatial data: methodology, challenges, and suggestions[J]. Tunnelling and Underground Space Technology, 2020, 100: 103393. [15] 唐泽强, 余江林, 任康. 综合地质物探方法在岩溶隧道超前地质预报中的应用[J]. 施工技术(中英文), 2025, 54(5): 68-72. TANG Zeqiang, YU Jianglin, REN Kang. Application of integrated geophysical exploration methods for advanced geological prediction in Karst Tunnel[J]. Construction Technology, 2025, 54(5): 68-72. [16] 李术才, 王鑫, 郭伟东, 等. 钻爆法机械化施工隧道随钻地震波超前地质探测技术研究[J]. 隧道建设(中英文), 2024, 44(4): 617-632. LI Shucai, WANG Xin, GUO Weidong, et al. An advance geological detection technology of seismic wave while drilling in mechanized tunnel construction by drilling and blasting method[J]. Tunnel Construction, 2024, 44(4): 617-632. [17] 廖铭, 周小兵. 基于TGS360Pro系统的EVS三维地质建模分析[J]. 交通科技与管理, 2024, 5(22): 4-6. [18] 张佳楠. 隧道地质勘察BIM三维建模技术研究[J]. 铁道建筑技术, 2024(1): 30-32. ZHANG Jianan. Technical research of BIM 3D modeling in tunnel geological survey[J]. Railway Construction Technology, 2024(1): 30-32. [19] ZHAO W L, TANG Y H, ZHAO S W. Application of geo-radar in the detection of various adverse geology in tunnel over-advance geological forecasting[J]. Journal of Physics: Conference Series, 2024, 2887(1): 012073. [20] LI S C, LIU B, XU X J, et al. An overview of ahead geological prospecting in tunneling[J]. Tunnelling and Underground Space Technology, 2017, 63: 69-94. [21] CHEN H H, LIU S M. Advanced geological prediction technology of tunnel based on image recognition[J]. Arabian Journal of Geosciences, 2019, 12(19): 601. [22] 徐晓雅, 王章琼, 李雷烈, 等. 山岭隧道地上地下一体化三维建模方法[J]. 科学技术与工程, 2024, 24(8): 3373-3380. XU Xiaoya, WANG Zhangqiong, LI Leilie, et al. A three-dimensional modeling method for mountain tunnel integration overground and underground[J]. Science Technology and Engineering, 2024, 24(8): 3373-3380. [23] YAO G, WU D. Reflection full waveform inversion[J]. Science China Earth Sciences, 2017, 60(10): 1783-1794. [24] HE B, LIU Y K, LU H Y, et al. Correlative full-intensity waveform inversion[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(10): 6983-6994. [25] HE W G, HU G H, ZHANG B. Optimal matching full waveform inversion[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5912410. [26] 任玉晓. 地震波速无监督深度学习反演方法及其在隧道超前探测中的应用[D]. 济南: 山东大学, 2021. REN Yuxiao. Unsupervised deep-learning inversion method for seismic velocity and its application in tunnel forward-prospecting[D]. Jinan: Shandong University, 2021. [27] 宋翱. 基于隧道掌子面的三维地震智能超前地质预报探测技术研究[D]. 北京: 中国地质大学(北京), 2020. SONG Ao. Research on intelligent advance prediction technology based on tunnel face using 3D seismic detection[D]. Beijing: China University of Geosciences, 2020. [28] CHOI S, YI D H, KIM D W, et al. Multi-source data fusion-driven urban building energy modeling[J]. Sustainable Cities and Society, 2025, 123: 106283. [29] 王浩, 毕聪威, 董士山, 等. 基于深度学习的隧道破碎围岩区域地质雷达目标检测研究[J]. 公路工程, 2025, 50(2): 67-76. WANG Hao, BI Congwei, DONG Shishan, et al. Research on GPR object detection in tunnel fractured surrounding rock area based on deep learning[J]. Highway Engineering, 2025, 50(2): 67-76. [30] 蒋源, 王海林, 陈兆. 基于深度学习的隧道不良地质体超前预报图像智能预测算法[J]. 现代隧道技术, 2024, 61(3): 148-156. JIANG Yuan, WANG Hailin, CHEN Zhao. Intelligent image analysis algorithm for advance forecasting of adverse geological bodies in tunnels based on deep learning[J]. Modern Tunnelling Technology, 2024, 61(3): 148-156. [31] 庙延钢, 李天华, 林培元. 云南铝厂隧道地表土石方爆破设计与施工[J]. 工程爆破, 1998, 4(1): 56-59. MIAO Yangang, LI Tianhua, LIN Peiyuan. Design and application of rock blasting on the rock above Yunnan Aluminum Plant tunnel[J]. Engineering Blasting, 1998, 4(1): 56-59. [32] 傅洪贤. 长距离小间距隧道爆破开挖设计与施工[J]. 工程爆破, 2006, 12(3): 30-32. FU Hongxian. Blasting design and construction of long distance with little space tunnel[J]. Engineering Blasting, 2006, 12(3): 30-32. [33] 王红梅, 东兆星, 苗永奕. 隧道掘进爆破图表计算机辅助设计[J]. 工程爆破, 2003, 9(3): 38-41. WANG Hongmei, DONG Zhaoxing, MIAOYongyi. Computer-aided design of drilling-and-blasting instruction and borehole pattern in tunneling[J]. Engineering Blasting, 2003, 9(3): 38-41. [34] 申佃友. 隧道工程控制爆破技术探讨与应用[D]. 成都: 西南交通大学, 2004. SHEN Dianyou. Discussion and apply about tunnel controlled blasting technology[D]. Chengdu: Southwest Jiaotong University, 2004. [35] 周杰. 软岩隧道光面爆破参数设计的数值模拟研究[J]. 成都大学学报(自然科学版), 2018, 37(4): 441-444. ZHOU Jie. Numerical simulation of smooth blasting parameters design for soft rock tunnel[J]. Journal of Chengdu University(Natural Science Edition), 2018, 37(4): 441-444. [36] 程光明. 隧道爆破方案优化设计控制超欠挖的研究[D]. 重庆: 重庆交通大学, 2015. CHENG Guangming. Research on the optimizing method of blasting to control the tunnel overbreak[D]. Chongqing: Chongqing Jiaotong University, 2015. [37] 朱敏, P. 法夫罗, P. 安德里厄. BLASTCAD──诺兰达公司的三维计算机辅助地下矿爆破设计系统(一)[J]. 国外金属矿山, 1994(1): 54-57. [38] 左静. 炮孔计算机辅助设计系统研究[J]. 矿业工程, 2009, 7(1): 62-63. ZUO Jing. Research on blast-hole computer-aided design system[J]. Mining Engineering, 2009, 7(1): 62-63. [39] 杨军, 李立杰, 刘红岩, 等. 露天台阶爆破设计智能化的探索[J]. 工程爆破, 2024, 30(5): 183-192. YANG Jun, LI Lijie, LIU Hongyan, et al. Exploration for intelligent bench blasting design in open-pit mine[J]. Engineering Blasting, 2024, 30(5): 183-192. [40] 王德胜. 爆破设计CAD技术[J]. 化工矿山技术, 1991(6):6-9. WANG Desheng. Blasting design CAD technology[J]. Industrial Minerals & Processing, 1991(6):6-9. [41] 龚建辉. 隧道掘进爆破设计与施工信息系统[D]. 成都: 西南交通大学, 2006. GONG Jianhui. The information system of tunneling blasting design and its construction [D]. Chengdu: Southwest Jiaotong University, 2006. [42] BAI R C, ZHANG P F, ZHANG Z Q, et al. Optimization of blasting parameters and prediction of vibration effects in open pit mines based on deep neural networks[J]. Alexandria Engineering Journal, 2023, 70: 261-271. [43] 王新民, 赵彬, 王贤来, 等. 基于BP神经网络的凿岩爆破参数优选[J]. 中南大学学报(自然科学版), 2009, 40(5): 1411-1416. WANG Xinmin, ZHAO Bin, WANG Xianlai, et al. Optimization of drilling and blasting parameters based on back-propagation neural network[J]. Journal of Central South University(Science and Technology), 2009, 40(5): 1411-1416. [44] 吴佳鑫. 基于岩体智能识别的隧道动态爆破设计方法与系统开发[D]. 沈阳: 沈阳工业大学, 2024. WU Jiaxin. Dynamic tunnel blasting design method and system development based on intelligent rock body recognition[D]. Shenyang: Shenyang University of Technology, 2024. [45] 贾连辉, 陈帅, 贾正文, 等. 钻爆法隧道智能建造体系及关键技术研究[J]. 隧道建设(中英文), 2023, 43(3): 392-407. JIA Lianhui, CHEN Shuai, JIA Zhengwen, et al. Research on intelligent construction systems and key technologies for drilling-and-blasting tunnels[J]. Tunnel Construction, 2023, 43(3): 392-407. [46] 王愁. 全液压凿岩台车设计及钻臂性能分析[D]. 徐州: 中国矿业大学, 2021. WANG Chou. Design of full hydraulic drilling jumbo and performance analysis for drill arm[D]. Xuzhou: China University of Mining and Technology, 2021. [47] 朱槟. 长大公路隧道施工机械化配套技术研究[J]. 西部交通科技, 2023(3): 161-164. ZHU Bin. Research on mechanized supporting technology of long highway tunnel construction[J]. Western China Communication Science & Technology, 2023(3): 161-164. [48] 朱建新, 何清华, 郭勇, 等. 液压凿岩设备的研制现状及其发展思路[J]. 凿岩机械气动工具, 1999(2):22-27. ZHU Jianxin, HE Qinghua, GUO Yong, et al. Development status and development ideas of hydraulic rock drilling equipment[J]. Rock Drilling Machinery & Pneumatic Tools, 1999(2):22-27. [49] 郑朝保, 张龙, 冯中兴, 等. 我国隧道凿岩设备的应用与发展[J]. 现代隧道技术, 2018, 55(4): 9-13. ZHENG Chaobao, ZHANG Long, FENG Zhongxing, et al. Development and application of rock-drilling equipment in China[J]. Modern Tunnelling Technology, 2018, 55(4): 9-13. [50] 周友行. 凿岩机器人孔序规划的研究与实现[D]. 长沙:中南大学, 2003. ZHOU youhang. The research and realization of the bore sequence planning in tunnel-rock-drilling robot [D]. Changsha:Central South University, 2003. [51] 张栋. 两种凿岩台车在使用过程中的适用性分析[J]. 凿岩机械气动工具, 2008(4): 59-61. ZHANG Dong. Applicability analysis of two kinds of rock drilling jumbo in use process[J]. Rock Drilling Machinery & Pneumatic Tools, 2008(4): 59-61. [52] 张达, 刘艾瑛. 中国采矿凿岩技术及设备研发趋势观察[EB/OL].(2015-05-15)[2025-06-30]. https://www.cnmn.com.cn/ShowNews1.aspx?id=318580 [53] 高志强, 郭治富. 国内外自动锚杆钻架类型特点及研究方向[J]. 煤炭科学技术, 2023, 51(3): 212-224. GAO Zhiqiang, GUO Zhifu. Type characteristics and research direction of automatic bolting frame[J]. Coal Science and Technology, 2023, 51(3): 212-224. [54] 曹天宇. 隧道凿岩台车主动源-破岩震源地震波场联合恢复方法及工程应用[D]. 济南: 山东大学, 2022. CAO Tianyu. Seismic wave field of active source-rock breaking source of tunnel drilling trolley joint recovery method and engineering application[D]. Jinan: Shandong University, 2022. [55] 韩玉辉. 液压凿岩台车自动定位钻孔关键技术研究[D]. 徐州: 中国矿业大学, 2019. HAN Yuhui. Research on key technologies of automatic location drilling for rock drilling jumbo[D]. Xuzhou: China University of Mining and Technology, 2019. [56] 刘泽鑫, 管会生. 凿岩台车钻臂工作空间求解[J]. 机械, 2012, 39(5):9-11. LIU Zexin, GUAN Huisheng. Workspace solution of drill jumbo boom[J]. Machinery, 2012, 39(5): 9-11. [57] 崔孟豪, 姬会福, 惠延波, 等. 基于RBF神经网络的七自由度凿岩台车钻臂运动学研究[J]. 机电工程, 2022, 39(9): 1312-1318. CUI Menghao, JI Huifu, HUI Yanbo, et al. Kinematics of 7-DOF rock drilling jumbo boom based on RBF neural network[J]. Journal of Mechanical & Electrical Engineering, 2022, 39(9): 1312-1318. [58] 姜天优, 杨聚辉, 邢亚伟, 等. 基于RBF神经网络凿岩台车钻臂逆解分析[J]. 矿山机械, 2023, 51(2): 1-6. JIANG Tianyou, YANG Juhui, XING Yawei, et al. Analysis on inverse kinematics solution of drilling arm of rock drilling jumbo based on RBF neural network[J]. Mining & Processing Equipment, 2023, 51(2): 1-6. [59] 张伟, 付文庆. 三臂凿岩台车钻孔路径优化研究[J]. 工程机械, 2022, 53(12): 32-39. ZHANG Wei, FU Wenqing. Research on drilling path optimization of three-boom drilling jumbo[J]. Construction Machinery and Equipment, 2022, 53(12): 32-39. [60] JIANG G J, CHEN H X, GAO L, et al. Reliability analysis on ammonium nitrate/fuel oil explosive vehicle pharmaceutical system based on dynamic fault tree and Bayesian network[J]. Annals of Operations Research, 2022, 311(1): 167-182. [61] TANG X Y, CHEN B, LI M J. Development and application of field mixing process and intelligent mixing vehicle for plateau type emulsified explosives for open pit mining[J]. Applied Mathematics and Nonlinear Sciences, 2024, 9(1): 20230251. [62] 王胜利, 刘犀斌, 任海燕. 现场混装乳化炸药在地下铁矿爆破中的应用[J]. 爆破器材, 2018, 47(6): 49-52. WANG Shengli, LIU Xibin, REN Haiyan. Application of on-site mixed emulsion explosive in underground blasting of iron mine[J]. Explosive Materials, 2018, 47(6): 49-52. [63] 田丰, 黄麟, 田惺哲, 等. 地下现场混装乳化炸药技术装备在西藏的应用[J]. 有色金属(矿山部分), 2021, 73(3): 129-132. TIAN Feng, HUANG Lin, TIAN Xingzhe, et al. Application of underground on-site mixing emulsion explosive technology and equipment in Tibet[J]. Nonferrous Metals(Mining Section), 2021, 73(3): 129-132. [64] 秦念稳. 钻爆法隧道炸药智能化装填系统研究与应用[J]. 铁道建筑技术, 2024(6): 175-178. QIN Nianwen. Research and application of intelligent explosives filling system for drilling-and-blasting tunnels[J]. Railway Construction Technology, 2024(6): 175-178. [65] 张天良. 紧握“施工锐器”建高铁示范工程[EB/OL].(2018-04-25)[2025-06-30]. http://tljsb.joyhua.cn/tljsb/20180425/html/content_20180425002001.htm [66] 冯有景, 吉学军, 梁锋, 等. 隧道工程中BCJ-2000(A)型现场混装乳化炸药车的应用实践[J]. 现代矿业, 2017, 33(8): 166-169. FENG Youjing, JI Xuejun, LIANG Feng, et al. The application practice of BCJ-2000(A)on-site mixed emulsion explosive truck in tunnel engineering[J]. Modern Mining, 2017, 33(8):166-169. [67] 郝亚飞, 薛里, 张小勇, 等. 现场混装乳化炸药在巷道掘进爆破中的试验研究[J]. 金属矿山, 2022(7): 58-63. HAO Yafei, XUE Li, ZHANG Xiaoyong, et al. Experimental study on on-site mixed emulsion explosive in underground roadways excavation blasting[J]. Metal Mine, 2022(7): 58-63. [68] 冷振东, 周桂松, 刘令, 等. 高原大断面隧道现场混装爆破关键技术研究[J]. 地下空间与工程学报, 2023,19(增刊2): 890-900. LENG Zhendong, ZHOU Guisong, LIU Ling, et al. Research on key techniques of mixed loading blasting in large cross section tunnels on plateau[J]. Chinese Journal of Underground Space and Engineering, 2023, 19(Suppl.2): 890-900. [69] 财联社. 壶化股份研制成功隧道爆破智能装药机器人[EB/OL].(2025-03-07)[2025-03-14]. https://www.163.com/dy/article/JQ25MH2005198CJN.html [70] 岳中文, 金庆雨, 潘杉, 等. 基于深度学习的轻量化炮孔智能检测方法[J]. 煤炭学报, 2024, 49(5): 2247-2256. YUE Zhongwen, JIN Qingyu, PAN Shan, et al. Intelligent detection method of lightweight blasthole based on deep learning[J]. Journal of China Coal Society, 2024, 49(5): 2247-2256. [71] LI R R, XU S, LI Z C, et al. Development and testing of self-swelling cartridge for use as stemming material in open-pit blasting—a quarry case study[J]. International Journal of Rock Mechanics and Mining Sciences, 2023, 170: 105503. [72] BALUCH K, PARK H J, KIM J G, et al. Enhancing rock blasting efficiency in mining and tunneling: a comparative study of shear-thickening fluid stemming and plug device performance[J]. Applied Sciences, 2024, 14(13): 5395. [73] CEVIZCI H. The environmental and ecological effects of the plaster stemming method for blasting: a case study[J]. Ekoloji, 2015: 17-22. [74] SHARMA S K, RAI P. Investigation of crushed aggregate as stemming material in bench blasting: a case study[J]. Geotechnical and Geological Engineering, 2015, 33(6): 1449-1463. [75] 任震, 程五一, 刘敦华, 等. 封堵灵-水压复合爆破在隧道施工中的应用[J]. 工程爆破, 2015, 21(4): 58-62. REN Zhen, CHENG Wuyi, LIU Dunhua, et al. The application of Fengduling and hydraulic composite blasting in tunnel construction[J]. Engineering Blasting, 2015, 21(4): 58-62. [76] 徐志成. 隧道水压爆破封堵材料研制试验及研究[J]. 铁道建筑技术, 2018(12): 114-116. XU Zhicheng. Development test of tunnel hydraulic blasting sealing material and its research[J]. Railway Construction Technology, 2018(12): 114-116. [77] LI P F, XIE S D, LU J J, et al. Research on the flow characteristics of blasthole stemming slurry in open-pit mining[J]. Frontiers in Earth Science, 2024, 12: 1430046. [78] BALUCH K, PARK H J, KIM J G, et al. Enhancing rock blasting efficiency in mining and tunneling: a comparative study of shear-thickening fluid stemming and plug device performance[J]. Applied Sciences, 2024, 14(13): 5395. [79] DING X H, AO Z C, ZHOU W, et al. Geopolymer-based modification of blasting sealing materials and optimization of blasting block size in coal seams of open pit mines[J]. International Journal of Mining Science and Technology, 2023, 33(12): 1551-1562. [80] KO Y, SHIN C, JEONG Y, et al. Blast hole pressure measurement and a full-scale blasting experiment in hard rock quarry mine using shock-reactive stemming materials[J]. Applied Sciences, 2022, 12(17): 8629. [81] KOJOVIC T. Influence of aggregate stemming in blasting on the SAG mill performance[J]. Minerals Engineering, 2005, 18(15): 1398-1404. [82] MA L, LAI X P, ZHANG J G, et al. Blast-casting mechanism and parameter optimization of a benched deep-hole in an opencast coal mine[J]. Shock and Vibration, 2020, 2020: 1396483. [83] CHEN M, YE Z W, WEI D, et al. The movement process and length optimization of deep-hole blasting stemming structure[J]. International Journal of Rock Mechanics and Mining Sciences, 2021, 146: 104836. [84] CHOUDHARY B S, AGRAWAL A. Minimization of blast-induced hazards and efficient utilization of blast energy by implementing a novel stemming plug system for eco-friendly blasting in open pit mines[J]. Natural Resources Research, 2022, 31(6): 3393-3410. [85] CEVIZCI H, OZKAHRAMAN H T. The effect of blast hole stemming length to rockpile fragmentation at limestone quarries[J]. International Journal of Rock Mechanics and Mining Sciences, 2012, 53: 32-35. [86] 王汪洋. 隧道聚能水压控制爆破岩机理与参数优化研究[D]. 南宁: 广西大学, 2019. WANG Wangyang. Study on rock breaking mechanism and parameter optimization of cumulative hydraulic controlled blasting in tunnel[D]. Nanning: Guangxi University, 2019. [87] 蒋建宏. 泥浆固化矿山充填材料的制备、 结构及性能研究[D]. 湘潭: 湖南科技大学, 2012. JIANG Jianhong. Study on preparation, structures and properties of mine backfill materials from mud solidification[D]. Xiangtan: Hunan University of Science and Technology, 2012. [88] 冯光明, 丁玉, 朱红菊, 等. 矿用超高水充填材料及其结构的实验研究[J]. 中国矿业大学学报, 2010, 39(6): 813-819. FENG Guangming, DING Yu, ZHU Hongju, et al. Experimental research on superhigh-water packing material for mining and its micromorphology[J]. Journal of China University of Mining & Technology, 2010, 39(6): 813-819. [89] 朱红兵. 空气间隔装药爆破机理及应用研究[D]. 武汉: 武汉大学, 2006. ZHU Hongbing. Study on the mechanism and application of air-decking blasting[D]. Wuhan: Wuhan University, 2006. [90] 张艳军, 雷美荣, 宁掌玄. 炮孔楔形体堵塞器研究[J]. 煤炭工程, 2015, 47(1): 60-62. ZHANG Yanjun, LEI Meirong, NING Zhangxuan. Study on wedge stemming plug of blast holes[J]. Coal Engineering, 2015, 47(1): 60-62. [91] 何广沂, 杨义东. 提高岩石爆破效果的国外炮泥塞介绍[J]. 爆破器材, 1998(5):37-38. HE Guangyi, YANG Yidong. Introduction of foreign stemming plug for improving rock blasting effect[J]. Explosive Materials, 1998(5):37-38. [92] LI X D, LIU K W, ZHAO X R, et al. Study on rock fracturing in smooth blasting under initial stress[J]. Engineering Fracture Mechanics, 2024, 296: 109865. [93] LU A, YAN P, LU W B, et al. Crack propagation mechanism of smooth blasting holes for tunnel excavation under high in-situ stress[J]. Engineering Fracture Mechanics, 2024, 304: 110144. [94] LI X D, LIU K W, QIU T, et al. Study of presplit blasting under high in-situ stress[J]. Engineering Fracture Mechanics, 2023, 288: 109360. [95] LIU K, LI Q Y, WU C Q, et al. Optimization of spherical cartridge blasting mode in one-step raise excavation using pre-split blasting[J]. International Journal of Rock Mechanics and Mining Sciences, 2020, 126: 104182. [96] ZHU F H, LIU Z G, ZUO Y F, et al. Damage and failure characteristics of coal and surrounding rock under shaped blasting[J]. Process Safety and Environmental Protection, 2023, 176: 56-64. [97] ZHU F H, LIU Z G, HUANG A C. Study on the coupling mechanism of shaped blasting and empty hole to crack coal body[J]. Process Safety and Environmental Protection, 2023, 175: 644-653. [98] LIU Y C, JIANG J C, HUANG A C, et al. Hazard assessment of the thermal stability of nitrification by-products by using an advanced kinetic model[J]. Process Safety and Environmental Protection, 2022, 160: 91-101. [99] YANG N, JIANG J C, HUANG A C, et al. Thermokinetic model-based experimental and numerical investigation of the thermal hazards of nitrification waste[J]. Journal of Loss Prevention in the Process Industries, 2022, 79: 104836. [100] ZHANG X Y, HU J Z, XUE H J, et al. Innovative approach based on roof cutting by energy-gathering blasting for protecting roadways in coal mines[J]. Tunnelling and Underground Space Technology, 2020, 99: 103387. [101] HAYES G A. Linear shaped-charge(LSC)collapse model[J]. Journal of Materials Science, 1984, 19(9): 3049-3058. [102] FOURNEY W L, DALLY J W, HOLLOWAY D C. Controlled blasting with ligamented charge holders[J]. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1978, 15(3): 121-129. [103] KIM Y, BRULAND A. Analysis and evaluation of tunnel contour quality index[J]. Automation in Construction, 2019, 99: 223-237. [104] 杨志坚. 隧道结构断面测量方法及对比分析[J]. 测绘通报, 2019(11): 160-162. YANG Zhijian. Methods and comparativeanalysis of tunnel structure section measuring[J]. Bulletin of Surveying and Mapping, 2019(11): 160-162. [105] 解玄, 张晓平, 唐少辉, 等. 基于拟蒙特卡洛法的隧道超欠挖体积精确计算研究[J/OL]. 武汉大学学报(工学版), 2024-03-27. https://link.cnki.net/urlid/42.1675.T.20240325.1652.002 XIE Xuan, ZHANG Xiaoping, TANG Shaohui, et al. Accurate calculation of overbreak and underbreak volume of tunnel based on quasi-monte carlo method[J]. Engineering Journal of Wuhan University, 2024-03-27. https://link.cnki.net/urlid/42.1675.T.20240325.1652.002 [106] 雷明锋, 张运波, 秦桂芳, 等. 山岭隧道爆破效果神经网络评价模型及爆破参数优化决策方法研究[J]. 现代隧道技术, 2023, 60(2):54-61. LEI Mingfeng, ZHANG Yunbo, QIN Guifang, et al. A study on neural network evaluation model of blasting effect in mountain tunnel and decision-making method for blasting parameter optimization[J]. Modern Tunnelling Technology, 2023, 60(2):54-61. [107] 何江, 孙海丽, 王解先, 等. 基于激光点云的隧道超欠挖检测与表达[J]. 工程勘察, 2025, 53(1):38-42. HE Jiang, SUN Haili, WANG Jiexian, et al. Detection and expression of tunnel overbreak and underbreak based on laser point clouds[J]. Geotechnical Investigation & Surveying, 2025, 53(1): 38-42. [108] 王铉彬, 李星星, 廖健驰, 等. 基于图优化的紧耦合双目视觉/惯性/激光雷达SLAM方法[J]. 测绘学报, 2022, 51(8): 1744-1756. WANG Xuanbin, LI Xingxing, LIAO Jianchi, et al. Tightly-coupled stereo visual-inertial-LiDAR SLAM based on graph optimization[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(8): 1744-1756. [109] HUANG Y C, LIU F, WANG J, et al. A photogrammetric system for tunnel underbreak and overbreak detection[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 22217-22226. [110] 王永琦. 基于机器学习的隧道光面爆破超欠挖预测研究[D]. 武汉: 武汉科技大学, 2024. WANG Yongqi. Research on prediction of overbreak and underbreak in tunnel smooth blasting Based on Machine learning[D]. Wuhan: Wuhan University of Science and Technology, 2024. [111] 张琦. 隧道爆破超欠挖预测模型及爆破参数优化方法研究[D]. 武汉: 武汉科技大学, 2024. ZHANG Qi. Research on prediction model of tunnel blasting overbreak and underbreak and optimization method of blasting parameters[D]. Wuhan: Wuhan University of Science and Technology, 2024. [112] 李华隆. 隧道聚能水压定向爆破动力响应特性及参数优化研究[D]. 南宁: 广西大学, 2022. LI Hualong. Study on dynamic response characteristics and parameter optimization of tunnel hydraulic shaped charge blasting[D]. Nanning: Guangxi University, 2022. [113] ZAKHAROV V, KUZNETSOV E A. Three-dimensional solitons[J]. Soviet Physics JETP, 1974, 29: 594-597. [114] 赵颖, 岳中文, 薛克军, 等. 基于特征选择的GS-KCV-XGBoost露天金属矿爆破块度预测模型[J]. 工程爆破, 2024, 30(6): 168-177. ZHAO Ying, YUE Zhongwen, XUE Kejun, et al. Prediction model of GS-KCV-XGBoost open pit metal mine blasting fragmentation based on feature selection[J]. Engineering Blasting, 2024, 30(6): 168-177. [115] 崔红艳, 张子禄, 胡静. 基于机器学习的爆破块度优化预测系统[J]. 软件, 2024, 45(7): 1-3. CUI Hongyan, ZHANG Zilu, HU Jing. Prediction system of blasting rocks fragmentaion based on machine learning[J]. Software, 2024, 45(7): 1-3. [116] 戴增杰, 梁昊, 王贵, 等. 基于3种神经网络算法的露天矿山台阶爆破块度预测[J]. 煤矿爆破, 2024, 42(4): 1-6. DAI Zengjie, LIANG Hao, WANG Gui, et al. Block size prediction for bench blasting in open-pit mine based on three neural network algorithms[J]. Coal Mine Blasting, 2024, 42(4): 1-6. [117] FRANKLIN J A. Measurement of blast fragmentation[M]. London, UK: Routledge, 1996: 73-78. [118] FRANKLIN J A. Measurement of blast fragmentation[M]. London, UK:Routledge, 1996: 101-108. [119] 王妍, 张瑞新, 孙健东, 等. 基于图像分割的露天煤矿爆堆块度评价方法[J]. 煤炭技术, 2024, 43(11): 95-98. WANG Yan, ZHANG Ruixin, SUN Jiandong, et al. Evaluation method of burst block degree in open-pit coal mine based on image segmentation[J]. Coal Technology, 2024, 43(11): 95-98. [120] HE P, XU Y F, JIANG F, et al. A rapid evaluation method of blasting effect based on optimized image segmentation algorithm and application in engineering[J]. Scientific Reports, 2024, 14(1): 4783. [121] 袁文华, 马芹永, 黄伟. 楔形掏槽微差爆破模型试验与分析[J]. 岩石力学与工程学报, 2012, 31(增刊1): 3352-3356. YUAN Wenhua, MA Qinyong, HUANG Wei. Model experiment and analysis of wedge-shaped cutting millisecond blasting [J]. Chinese Journal of Rock Mechanics and Engineering, 2012, 31(Suppl.1): 3352-3356. [122] 杨玉银. 提高隧洞开挖爆破钻孔利用率的方法[J]. 爆破, 2014, 31(2): 72-74. YANG Yuyin. Method of increasing blasting and drilling utilization ratio in tunnel excavation[J]. Blasting, 2014, 31(2): 72-74. [123] YU B B, WANG B, LI Y, et al. Prediction of blast-hole utilization rate using structured nonlinear support vector machine combined with optimization algorithms[J]. Applied Intelligence, 2024, 54(19): 9136-9157. [124] 岳中文, 范皓宇, 马鑫民. 基于PSO-SVM的煤矿巷道爆破效果预测关键技术研究[J]. 爆破, 2019, 36(3): 31-36. YUE Zhongwen, FAN Haoyu, MA Xinmin. Research on key technologies of blasting effect prediction of coal mine roadway based on PSO-SVM[J]. Blasting, 2019, 36(3): 31-36.