Article(id=1314907113688756281, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314907112854089785, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2025.06.01, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1748534400000, receivedDateStr=2025-05-30, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791427885696, onlineDateStr=2026-10-08, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791427885696, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791427885696, creator=13701087609, updateTime=1791427885696, updator=13701087609, issue=Issue{id=1314907112854089785, tenantId=1146029695717560320, journalId=1235980550691926019, year='2025', volume='45', issue='6', pageStart='1', pageEnd='228', issueExtLink='null', onlineDate='null', pubDate='1764518400000', pubDateStr='2025-12-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791427885497, creator='13701087609', updateTime=1791430521754, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314918170201252492, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314907112854089785, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314918170201252493, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314907112854089785, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1, endPage=7, ext={EN=ArticleExt(id=1314907115492307002, articleId=1314907113688756281, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Current Status and Prospects of Application of Intelligent Technologies in Safety Management of Non-coal Mines, columnId=1236276106018484431, journalTitle=Mining and Metallurgical Engineering, columnName=MINING, runingTitle=null, highlight=null, articleAbstract=

This paper presents the evolution path of intelligent technologies, from automated monitoring at early stage to modern AI-based decision support, and focuses on analysis of research results and application cases of key technologies, such as neural networks, the Internet of Things (IoT), digital twins and big data. It also presents discussion of the latest progress in application of a new generation of intelligent technologies represented by machine learning in safety management of non-coal mines. Specifically, technologies including deep neural networks, support vector machines, decision trees and random forests have shown advantages in aspects such as personnel safety management and positioning, monitoring and early warning of mine disasters, safe operation of mine equipment, and safety in mine blasting operation. Finally, the development trends of non-coal mine safety management are proposed, in terms of in-depth application and integration of intelligent technologies, compatibility of old equipment with modern intelligent technologies, and integrated management.

, authors=Xiaoshuang LI1, Haochun ZANG1, Yunmin WANG2, Jianpeng LIU1, authorsList=Xiaoshuang LI, Haochun ZANG, Yunmin WANG, Jianpeng LIU, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314907115777519675, articleId=1314907113688756281, tenantId=1146029695717560320, journalId=1235980550691926019, language=CN, title=非煤矿山安全管理中智能化技术的应用现状与展望, columnId=1236276106219811026, journalTitle=矿冶工程杂志, columnName=采矿, runingTitle=null, highlight=null, articleAbstract=

系统梳理了智能化技术从初期自动化监测到现代智能决策支持的演进路径,重点分析了神经网络、物联网、数字孪生、大数据等关键技术的研究成果与应用实例;探讨了以机器学习为代表的新一代智能化技术在非煤矿山安全管理中的应用进展,包括深度神经网络、支持向量机、决策树和随机森林等技术在人员安全管理与定位、矿山灾害监测与预警、矿山设备运行安全和矿山爆破作业安全等方面展现出的优势,展望了未来非煤矿山安全管理在智能化技术深度应用与融合、旧设备与现代智能技术兼容及系统化集成管理方面的发展趋势。

, authors=李小双1, 臧浩淳1, 王运敏2, 刘健鹏1, authorsList=李小双, 臧浩淳, 王运敏, 刘健鹏, authorCompany=null, correspAuthors=null, authorNote=

李小双(1983—),男,湖北随州人,博士,教授,主要从事矿山岩土工程方面的研究工作。E-mail:

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非煤矿山安全管理中智能化技术的应用现状与展望
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李小双 1 , 臧浩淳 1 , 王运敏 2 , 刘健鹏 1
矿冶工程杂志 | 采矿 2025,45(6): 1-7
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矿冶工程杂志 |采矿 2025 , 45 (6) : 1 -7
非煤矿山安全管理中智能化技术的应用现状与展望
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李小双1 , 臧浩淳1, 王运敏2, 刘健鹏1
作者信息
  • 1.常州大学城市建设学院,江苏 常州 213164
  • 2.金属矿山安全与健康国家重点实验室,安徽 马鞍山 243000
作者简介:

李小双(1983—),男,湖北随州人,博士,教授,主要从事矿山岩土工程方面的研究工作。E-mail:

Current Status and Prospects of Application of Intelligent Technologies in Safety Management of Non-coal Mines
Xiaoshuang LI1 , Haochun ZANG1, Yunmin WANG2, Jianpeng LIU1
Affiliations
  • 1.School of Urban Construction, Changzhou University, Changzhou 213164, Jiangsu, China
  • 2.State Key Laboratory of Safety and Health for Metal Mines, Ma'anshan 243000, Anhui, China
doi: 10.3969/j.issn.0253-6099.2025.06.01
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系统梳理了智能化技术从初期自动化监测到现代智能决策支持的演进路径,重点分析了神经网络、物联网、数字孪生、大数据等关键技术的研究成果与应用实例;探讨了以机器学习为代表的新一代智能化技术在非煤矿山安全管理中的应用进展,包括深度神经网络、支持向量机、决策树和随机森林等技术在人员安全管理与定位、矿山灾害监测与预警、矿山设备运行安全和矿山爆破作业安全等方面展现出的优势,展望了未来非煤矿山安全管理在智能化技术深度应用与融合、旧设备与现代智能技术兼容及系统化集成管理方面的发展趋势。

矿山安全  /  非煤矿山  /  智能化技术  /  安全管理  /  机器学习  /  发展趋势

This paper presents the evolution path of intelligent technologies, from automated monitoring at early stage to modern AI-based decision support, and focuses on analysis of research results and application cases of key technologies, such as neural networks, the Internet of Things (IoT), digital twins and big data. It also presents discussion of the latest progress in application of a new generation of intelligent technologies represented by machine learning in safety management of non-coal mines. Specifically, technologies including deep neural networks, support vector machines, decision trees and random forests have shown advantages in aspects such as personnel safety management and positioning, monitoring and early warning of mine disasters, safe operation of mine equipment, and safety in mine blasting operation. Finally, the development trends of non-coal mine safety management are proposed, in terms of in-depth application and integration of intelligent technologies, compatibility of old equipment with modern intelligent technologies, and integrated management.

mine safety  /  non-coal mine  /  intelligent technology  /  safety management  /  machine learning  /  development trend
李小双, 臧浩淳, 王运敏, 刘健鹏. 非煤矿山安全管理中智能化技术的应用现状与展望. 矿冶工程杂志, 2025 , 45 (6) : 1 -7 . DOI: 10.3969/j.issn.0253-6099.2025.06.01
Xiaoshuang LI, Haochun ZANG, Yunmin WANG, Jianpeng LIU. Current Status and Prospects of Application of Intelligent Technologies in Safety Management of Non-coal Mines[J]. Mining and Metallurgical Engineering, 2025 , 45 (6) : 1 -7 . DOI: 10.3969/j.issn.0253-6099.2025.06.01
  • 云南省中央引导地方科技发展项目(202407AC110019)
  • 国家自然科学基金(42477142; 42277154)
  • 江苏省中青年学术带头人项目(SCZ2509200010)
  • 山东省高等学校“青创人才引育计划”(鲁教科函〔2021〕51号)
  • 山东省自然科学基金(ZR2022ME188)
  • 济南市“新高校20条”科研带头人工作室项目(20228108)
  • 常州大学高层次人才引进项目(ZMF24020037)
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2025年第45卷第6期
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doi: 10.3969/j.issn.0253-6099.2025.06.01
  • 接收时间:2025-05-30
  • 首发时间:2026-10-08
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  • 收稿日期:2025-05-30
基金
云南省中央引导地方科技发展项目(202407AC110019)
国家自然科学基金(42477142; 42277154)
江苏省中青年学术带头人项目(SCZ2509200010)
山东省高等学校“青创人才引育计划”(鲁教科函〔2021〕51号)
山东省自然科学基金(ZR2022ME188)
济南市“新高校20条”科研带头人工作室项目(20228108)
常州大学高层次人才引进项目(ZMF24020037)
作者信息
    1.常州大学城市建设学院,江苏 常州 213164
    2.金属矿山安全与健康国家重点实验室,安徽 马鞍山 243000
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https://castjournals.cast.org.cn/joweb/kygczz/CN/10.3969/j.issn.0253-6099.2025.06.01
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2种不同金属材料的力学参数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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