Article(id=1321897375522738203, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321897310649434924, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1772899200000, receivedDateStr=2026-03-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793094493990, onlineDateStr=2026-10-27, pubDate=1790265600000, pubDateStr=2026-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793094493990, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793094493990, creator=13701087609, updateTime=1793094493990, updator=13701087609, issue=Issue{id=1321897310649434924, tenantId=1146029695717560320, journalId=1225396423026438145, year='2026', volume='46', issue='9', pageStart='1', pageEnd='346', issueExtLink='null', onlineDate='null', pubDate='1790265600000', pubDateStr='2026-09-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1793094478523, creator='13701087609', updateTime=1793094618231, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321897896698561428, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321897310649434924, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321897896698561429, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321897310649434924, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=274, endPage=281, ext={EN=ArticleExt(id=1321897375917002780, articleId=1321897375522738203, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Research and Application of Data Penetration-Driven Digital-Intelligent Supervision Mode for Dual Prevention Mechanism in Non-Coal Mines, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To address prominent problems prevalent at the regulatory end of the dual-prevention mechanism, including data island, risk identification relying on fixed thresholds, and difficulties in penetrating enterprise underlying data, and to explore an effective path for digital-intelligent transformation of the regulatory end, a four-level regulatory framework of "data penetration-early warning grading-closed-loop response-law-enforcement implementation" was proposed. By realizing real-time interconnection between enterprise underlying sensing data and the regulatory end, this framework conducts cross-verification on the authenticity of hazard investigation, rectification management and monitoring data using methods such as spatio-temporal behavior verification, spatial static verification, and data consistency verification. On this basis, an early warning comprehensive index model was established to realize dynamic risk identification and hierarchical response. At the same time, a differentiated and accurate law enforcement path based on a digital evidence chain and "dynamic safety risk profile" was explored to improve the timeliness and accuracy of supervision. The empirical results show that this model improves the efficiency of mine supervision by more than 60% and effectively reduces the frequency of accidents. It provides a scientific scheme for promoting the transformation of the dual prevention mechanism from formal operation to substantive operation, and provides a feasible path for building a more efficient and intelligent safety governance system for non-coal mines.

, authors=Xu Sun¹, Shuangqing Zhang², Qingqiong Yan³, authorsList=Xu Sun, Shuangqing Zhang, Qingqiong Yan, 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=1321897376600674333, articleId=1321897375522738203, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=数据穿透驱动的非煤矿山双重预防机制数智化监管模式研究与应用, columnId=1226462295946085268, journalTitle=矿业研究与开发, columnName=矿山机电与矿业智能化, runingTitle=null, highlight=null, articleAbstract=

为解决双重预防机制在监管端普遍存在的数据孤岛、风险识别依赖固定阈值、难以穿透企业底层数据等突出问题，探索监管端数智化转型的有效路径，提出“数据穿透—分级预警—响应闭环—执法落地”四级监管框架。该框架通过实现企业底层感知数据与监管端的实时互联，利用时空行为验证、空间静态验证、数据一致性验证等方法，对隐患排查、整改治理及监测数据真实性进行交叉校验。在此基础上，建立预警综合指数模型，实现风险动态识别与分级响应，同时探索基于数字化证据链与“安全风险动态画像”的差异化精准执法路径，提升监管的及时性和精准度。实证结果表明，该模式使矿山监管效能提升超60%，有效降低了事故发生频次，为推动双重预防机制从形式运行向实质运行转变提供了科学方案，为建设更加高效、智能的非煤矿山安全治理体系提供了可行路径。

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孙旭（1986一），男，辽宁盘锦人，工程师，主要从事非煤矿山安全监管工作。E-mail:czfm2199782@163.com

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孙旭（1986一），男，辽宁盘锦人，工程师，主要从事非煤矿山安全监管工作。E-mail:czfm2199782@163.com

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