马鑫民,杨国梁,刘伟,杨立云
MA Xin-min,YANG Guo-liang,LIU Wei,YANG Li-yun

• 1:中国矿业大学(北京)力学与建筑工程学院

摘要(Abstract)：

为克服爆破工程教学实践性强、安全标准高的局限性，开展爆破工程决策系统的研究与构建，采用多源知识融合技术建立了爆破工程综合数据库。运用机器学习和计算机技术开发了爆破工程智能决策系统，设计了关键指标输入、方案推理、爆破图表自动生成等3个模块，实现不同地质条件下的爆破方案的智能设计和工程图表的自动绘制。以直观、仿真的形式，帮助学生清楚地了解爆破工程设计的原理，掌握影响爆破方案设计的关键因素，爆破工程图表绘制标准等，提高了学生的计算机辅助综合应用能力与自主创新意识，改善了教学效果。
To overcome the limitations of teaching blasting engineering with its high practicality and safety standards, research and construction of a decision system for blasting engineering were carried out. A comprehensive database of blasting engineering was established using multi-source knowledge fusion technology. The intelligent decision-making system for blasting engineering was developed by using machine learning and computer technology, and three modules were designed for key index input, scheme reasoning, and automatic generation of blasting diagrams to realize the intelligent design of blasting schemes and mechanical drawing of engineering diagrams under different geological conditions. It is more intuitive and simulated to help students understand the principles of blasting engineering design, master the key factors affecting the design of blasting solutions and standards for drawing blasting engineering diagrams. It improves the students' comprehensive computer application ability and sense of independent innovation, enhancing the teaching effect.

关键词(KeyWords)： 机器学习;爆破工程;教学系统;实践
machine learning;blasting engineering;teaching and learning system;practice

Abstract:

Keywords:

基金项目(Foundation): 中国矿业大学(北京)教改基金资助项目(J210604、J20ZD20、J200701)

作者(Author): 马鑫民,杨国梁,刘伟,杨立云
MA Xin-min,YANG Guo-liang,LIU Wei,YANG Li-yun

DOI: 10.19931/j.EB.20220264

参考文献(References)：

• [1] 张宁，舒涵.《爆破工程》的教学探讨与实践[J].科技经济导刊，2016,24(28):124.ZHANG N,SHU H.Teaching discussion and practice of Blasting Engineering[J].Technology and Economic Guide,2016,24(28):124.
• [2] 张飞燕，杨小林，韩颖，等.巷道掘进爆破安全虚拟仿真实验教学平台构建[J].实验技术与管理，2020,37(6):151-156.ZHANG F Y,YANG X L,HAN Y,et al.Construction of virtual simulation experiment teaching platform for safety of roadway excavation blasting[J].Experimental Technology and Management,2020,37(6):151-156.
• [3] 王玉杰.爆破工程[M].武汉：武汉理工大学出版社，2018.WANG Y J.Blasting engineering[M].Wuhan:Wuhan University of Technology Press,2018.
• [4] 新华社.习近平：给广大科学家和科技工作者搭建施展才华的舞台[J].中国人才，2020(10):2.Xinhua News Agency.XI Jinping:Building a stage for scientists and science and technology workers to display their talents[J].Chinese Talents,2020(10):2.
• [5] 叶海旺，雷涛，李梅，等.爆破工程虚拟仿真实验系统及教学实践研究[J].爆破，2020,37(3):153-158.YE H W,LEI T,LI M,et al.Research on virtual simulation experiment system and teaching practice of blasting engineering[J].Blasting,2020,37(3):153-158.
• [6] 谢先启.拆除爆破技术的发展与展望[J].爆破，2019,36(2) :1-12.XIE X Q.Development and prospects of demolition and blasting technology[J].Blasting,2019,36(2) :1-12.
• [7] 徐洁磐.数据库系统原理[M].上海：上海科学技术文献出版社，1997:116-132.XU J P.Database system principles[M].Shanghai:Shanghai Scientific and Technologial Literature Press,1997:116-132.
• [8] 孙江宏，何宇凡，王佳林，等.管道检测机器人虚拟仿真实验系统设计[J].实验技术与管理，2021,38(9):138-142.SUN J H,HE Y F,WANG J L,et al.Design of a virtual simulation experimental system for pipeline inspection robots[J].Experimental Technology and Management,2021,38(9):138-142.
• [9] 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):31-36,55.YUE Z W,FAN H Y,MA X M.Research on the key technology of prediction of coal mine roadway blasting effect based on PSO-SVM[J].Blasting,2019,36(3):31-36,55.
• [10] DING X,LI K,XIAO S,et al.Analysis of key technologies and development of integrated digital processing system for cast blasting design[J].Cent.South Univ.,2015,22:1 037-1 044.
• [11] 李晓强，崔德光.基于关系数据库的知识库结构设计[J].计算机工程与应用，2001,24:102-103.LI X Q,CUI D G.Knowledge base structure design based on relational database[J].Computer Engineering and Applications,2001,24:102-103.
• [12] 杨仁树，马鑫民，李清，等.煤矿巷道掘进爆破智能设计系统及应用[J].煤炭学报，2013,38(7):1 130-1 135.YANG R S,MA X M,LI Q,et al.Intelligent design system and application of blasting for coal mine roadway excavation [J].Journal of China Coal Society,2013,38(7):1 130-1 135.
• [13] 戴俊.爆破工程[M].北京：机械工业出版社，2015.DAI J.Blasting engineering[M].Beijing:Machinery Industry Press,2015.
• [14] 汪旭光.论合理的炸药单耗[J].有色金属(矿山部分),1982,34(5):31-33.WANG X G.Discussion on reasonable unit consumption of explosives[J].Nonferrous Metals(Mining Section),1982,34(5):31-33.
• [15] WU Z,LUO D,CHEN G.Design and realization of the intelligent design system for tunnel blasting in mine based on database[J].Geofluids,2020,(4):11.
• [16] 国家安全生产监督管理总局.爆破安全规程：GB 6722—2014[S].北京：中国标准出版社，2015.State Administration of Work Satefy.Safety regulations for blasting:GB 6722—2014[S].Beijing:Standards Press of China,2015.
• [17] 马鑫民，王毅，翟中华，等.岩石巷道爆破效果预测及应用效果实践研究[J].煤炭工程，2022,54(4):92-98.MA X M,WANG Y,ZHAI Z H,et al.Forecast model of rock roadway blasting effect and its application result[J].Coal Engineering,2022,54(4):92-98.
• [18] JIA C,ZHANG Y,SHI F,et al.Light field imaging based on a parallel SVM method for recognizing 2D fake pedestrians[J].Optoelectronics Letters,2022,18(1):48-53.
• [19] 余聪，宋晋东，李山有.基于支持向量机的现地地震预警地震动峰值预测[J].振动与冲击，2021,40(3):63-72,80.YU C,SONG J D,LI S Y.Prediction of peak ground motion for on-site earthquake early warning based on SVM[J].Journal of Vibration and Shock,2021,40(3):63-72,80.
• [20] 孙立军，刘悦，童杰林，等.基于科氏流量计和PSO-SVM的气液两相流测量研究[J].天津大学学报(自然科学与工程技术版),2022,55(10):1 034-1 044.SUN L J,LIU Y,TONG J L,et al.Gas-liquid two-phase flow measurement based on coriolis flowmeters and PSO-SVM[J].Journal of Tianjin University (Science and technology),2022,55(10):1 034-1 044.