Article(id=1149738623953711671, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149738621005119786, articleNumber=1003-3033(2024)09-0009-10, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.09.0208, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710864000000, receivedDateStr=2024-03-20, revisedDate=1719158400000, revisedDateStr=2024-06-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1752048649061, onlineDateStr=2025-07-09, pubDate=1727452800000, pubDateStr=2024-09-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752048649061, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752048649061, creator=13701087609, updateTime=1752048649061, updator=13701087609, issue=Issue{id=1149738621005119786, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='9', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752048648358, creator=13701087609, updateTime=1757401551172, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1172190322751816581, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149738621005119786, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1172190322751816582, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149738621005119786, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=9, endPage=18, ext={EN=ArticleExt(id=1149738624180204090, articleId=1149738623953711671, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Statistical analysis and countermeasures of major accidents in coal mines in China, columnId=1149733271128420907, journalTitle=China Safety Science Journal, columnName=Safety social science and safety management, runingTitle=null, highlight=null, articleAbstract=

To reveal the characteristics of coal mine accidents in China in recent years,and put forward targeted countermeasures and suggestions for accident prevention,firstly,the major and catastrophic coal mine accidents in China from 2013 to 2023 were collected and analyzed from the aspects of the year,type,month,province and cause of the accident. Secondly,taking "2·22" particularly serious collapse accident in Inner Mongolia Xinjing coal mine as an example,the accident was analyzed based on 24Model. Finally,combined with the above analysis and research results,the accident prevention countermeasures and suggestions in line with the current situation of coal mine safety production in China were put forward. The analysis and research results show that the number of major accidents and deaths in coal mines has shown an overall downward trend,and the level of coal mine safety production in China has significantly improved since the 12th Five Year Plan. Gas accidents are still the main accidents in coal mines in China,accounting for 51%. The fourth quarter of each year is a period of high incidence of coal mine accidents,accounting for 30.43% of the total number of accidents. Affected by geological conditions and occurrence,accidents often occur in the main coal producing areas. The proportion of accidents caused by unsafe human behavior is as high as 74%. When there are hidden dangers at both the individual and organizational levels and the dual prevention measures are not in place,accidents are likely to occur. Countermeasures and suggestions for reducing coal mine safety accidents are put forward from four dimensions,including safety supervision,strengthening safety through science and technology,team development and safety culture.

, correspAuthors=Yingjie LIU, 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, authorCompany=null, fund=null, authors=null, authorsList=Haijun WANG, Qingjie QI, Yuntao LIANG, Qingxin QI, Yingjie LIU, Zuo SUN), CN=ArticleExt(id=1149738648435864017, articleId=1149738623953711671, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=我国煤矿重特大事故统计分析及对策建议, columnId=1149733271296193071, journalTitle=中国安全科学学报, columnName=安全社会科学与安全管理, runingTitle=null, highlight=null, articleAbstract=

为揭示近年来我国煤矿事故特征,有针对性地提出事故防范对策建议,首先,收集整理2013—2023年全国重特大煤矿事故,分析事故发生的年份、类型、月份、省份和原因等方面;其次,以内蒙古新井煤业“2·22”特别重大坍塌事故为例,基于“2-4”模型(24Model)分析导致事故发生的原因;最后,结合以上分析和研究结果提出符合我国现阶段煤矿安全生产形势的事故预防对策与建议。结果表明:煤矿重特大事故发生起数和死亡人数呈整体下降趋势,且进入“十二五”规划以来,我国煤矿安全生产水平明显提高;瓦斯事故仍是我国煤矿主要事故,占事故总起数的51%;每年第4季度是煤矿事故高发期,占事故总起数的30.43%;受地质条件和赋存情况影响,煤炭主要产区发生事故较多;人的不安全行为导致的事故占比高达74%;当个体层面和组织层面存在隐患且双重预防措施不到位时,易发生事故;从安全监管、科技兴安、队伍建设、安全文化等4个维度提出降低煤矿安全事故的对策建议。

, correspAuthors=刘英杰, authorNote=null, correspAuthorsNote=
** 刘英杰(1985—),男,内蒙古通辽人,博士,研究员,主要从事煤矿灾害监测预警与防控、应急管理、应急救援技术与装备的研究与开发应用。E-mail:
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王海军 (1975—),男,山东安丘人,博士,研究员,主要从事煤矿数字化、自动化、信息化、矿山机械智能化、煤矿机器人等理论、技术与装备的研究与开发。E-mail:

齐庆杰,教授;

梁运涛,研究员;

齐庆新,研究员;

孙祚,助理研究员

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王海军 (1975—),男,山东安丘人,博士,研究员,主要从事煤矿数字化、自动化、信息化、矿山机械智能化、煤矿机器人等理论、技术与装备的研究与开发。E-mail:

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王海军 (1975—),男,山东安丘人,博士,研究员,主要从事煤矿数字化、自动化、信息化、矿山机械智能化、煤矿机器人等理论、技术与装备的研究与开发。E-mail:

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齐庆杰,教授;

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梁运涛,研究员;

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梁运涛,研究员;

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齐庆新,研究员;

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齐庆新,研究员;

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孙祚,助理研究员

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孙祚,助理研究员

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Statistics of major accidents in coal mines from 2013 to 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
年份 重大事
故起数
重大事
故死亡
人数
特大事
故起数
特大事
故死亡
人数
原煤产
量/
亿t
百万吨
死亡率
2013 13 209 1 36 39.7 0.293
2014 14 228 0 0 38.7 0.257
2015 5 84 0 0 37.5 0.159
2016 9 130 2 65 33.6 0.156
2017 7 87 0 0 35.2 0.106
2018 2 34 0 0 36.8 0.093
2019 4 74 0 0 39.7 0.083
2020 3 52 0 0 38.4 0.058
2021 2 41 0 0 40.7 0.044
2022 2 24 0 0 45.6 0.054
2023 4 50 1 53 47.1 0.094
合计 65 1013 4 154
), ArticleFig(id=1167865513402179982, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738623953711671, language=CN, label=表1, caption=

2013—2023年煤矿重特大事故统计

, figureFileSmall=null, figureFileBig=null, tableContent=
年份 重大事
故起数
重大事
故死亡
人数
特大事
故起数
特大事
故死亡
人数
原煤产
量/
亿t
百万吨
死亡率
2013 13 209 1 36 39.7 0.293
2014 14 228 0 0 38.7 0.257
2015 5 84 0 0 37.5 0.159
2016 9 130 2 65 33.6 0.156
2017 7 87 0 0 35.2 0.106
2018 2 34 0 0 36.8 0.093
2019 4 74 0 0 39.7 0.083
2020 3 52 0 0 38.4 0.058
2021 2 41 0 0 40.7 0.044
2022 2 24 0 0 45.6 0.054
2023 4 50 1 53 47.1 0.094
合计 65 1013 4 154
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我国煤矿重特大事故统计分析及对策建议
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王海军 , 齐庆杰 , 梁运涛 , 齐庆新 , 刘英杰 ** , 孙祚
中国安全科学学报 | 安全社会科学与安全管理 2024,34(9): 9-18
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中国安全科学学报 | 安全社会科学与安全管理 2024, 34(9): 9-18
我国煤矿重特大事故统计分析及对策建议
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王海军 , 齐庆杰, 梁运涛, 齐庆新, 刘英杰** , 孙祚
作者信息
  • 煤炭科学研究总院有限公司,北京 100013
  • 王海军 (1975—),男,山东安丘人,博士,研究员,主要从事煤矿数字化、自动化、信息化、矿山机械智能化、煤矿机器人等理论、技术与装备的研究与开发。E-mail:

    齐庆杰,教授;

    梁运涛,研究员;

    齐庆新,研究员;

    孙祚,助理研究员

通讯作者:

** 刘英杰(1985—),男,内蒙古通辽人,博士,研究员,主要从事煤矿灾害监测预警与防控、应急管理、应急救援技术与装备的研究与开发应用。E-mail:
Statistical analysis and countermeasures of major accidents in coal mines in China
Haijun WANG , Qingjie QI, Yuntao LIANG, Qingxin QI, Yingjie LIU** , Zuo SUN
Affiliations
  • Chinese Institute of Coal Science,Beijing 100013,China
出版时间: 2024-09-28 doi: 10.16265/j.cnki.issn1003-3033.2024.09.0208
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为揭示近年来我国煤矿事故特征,有针对性地提出事故防范对策建议,首先,收集整理2013—2023年全国重特大煤矿事故,分析事故发生的年份、类型、月份、省份和原因等方面;其次,以内蒙古新井煤业“2·22”特别重大坍塌事故为例,基于“2-4”模型(24Model)分析导致事故发生的原因;最后,结合以上分析和研究结果提出符合我国现阶段煤矿安全生产形势的事故预防对策与建议。结果表明:煤矿重特大事故发生起数和死亡人数呈整体下降趋势,且进入“十二五”规划以来,我国煤矿安全生产水平明显提高;瓦斯事故仍是我国煤矿主要事故,占事故总起数的51%;每年第4季度是煤矿事故高发期,占事故总起数的30.43%;受地质条件和赋存情况影响,煤炭主要产区发生事故较多;人的不安全行为导致的事故占比高达74%;当个体层面和组织层面存在隐患且双重预防措施不到位时,易发生事故;从安全监管、科技兴安、队伍建设、安全文化等4个维度提出降低煤矿安全事故的对策建议。

煤矿  /  重特大事故  /  统计分析  /  “2-4”模型(24Model)  /  事故原因  /  不安全行为

To reveal the characteristics of coal mine accidents in China in recent years,and put forward targeted countermeasures and suggestions for accident prevention,firstly,the major and catastrophic coal mine accidents in China from 2013 to 2023 were collected and analyzed from the aspects of the year,type,month,province and cause of the accident. Secondly,taking "2·22" particularly serious collapse accident in Inner Mongolia Xinjing coal mine as an example,the accident was analyzed based on 24Model. Finally,combined with the above analysis and research results,the accident prevention countermeasures and suggestions in line with the current situation of coal mine safety production in China were put forward. The analysis and research results show that the number of major accidents and deaths in coal mines has shown an overall downward trend,and the level of coal mine safety production in China has significantly improved since the 12th Five Year Plan. Gas accidents are still the main accidents in coal mines in China,accounting for 51%. The fourth quarter of each year is a period of high incidence of coal mine accidents,accounting for 30.43% of the total number of accidents. Affected by geological conditions and occurrence,accidents often occur in the main coal producing areas. The proportion of accidents caused by unsafe human behavior is as high as 74%. When there are hidden dangers at both the individual and organizational levels and the dual prevention measures are not in place,accidents are likely to occur. Countermeasures and suggestions for reducing coal mine safety accidents are put forward from four dimensions,including safety supervision,strengthening safety through science and technology,team development and safety culture.

coal mine  /  major accident  /  statistical analysis  /  "2-4" model (24Model)  /  accident cause  /  unsafe behavior
王海军, 齐庆杰, 梁运涛, 齐庆新, 刘英杰, 孙祚. 我国煤矿重特大事故统计分析及对策建议. 中国安全科学学报, 2024 , 34 (9) : 9 -18 . DOI: 10.16265/j.cnki.issn1003-3033.2024.09.0208
Haijun WANG, Qingjie QI, Yuntao LIANG, Qingxin QI, Yingjie LIU, Zuo SUN. Statistical analysis and countermeasures of major accidents in coal mines in China[J]. China Safety Science Journal, 2024 , 34 (9) : 9 -18 . DOI: 10.16265/j.cnki.issn1003-3033.2024.09.0208
煤矿是安全生产的重中之重,近年来随着科技水平的不断提高,我国煤矿安全生产形势持续稳定好转,但重特大事故时有发生,安全生产形势依然严峻[1-2]。2022年,全国共发生煤矿事故168起、死亡245人,同比分别上升85%和38%,全国煤矿百万吨死亡率为0.054[3]。相比之下,2020年美国因煤矿安全生产事故造成的死亡人数仅为5人[4]。2023年9月,《关于进一步加强矿山安全生产工作的意见》指出,着力从根本上消除事故隐患、解决实际问题,加强源头管控,防范化解风险。通过统计分析煤矿安全事故,总结事故发生特征,对于加强新时期煤矿安全生产工作具有重要意义。
目前,国内专家学者针对煤矿事故统计分析开展了诸多研究[5-11],例如:赵亚军等[8]统计整理2010—2021年我国煤矿安全事故,从事故发生的级别、类型、时间和地域等方面分析事故发生的普遍特征,提出了煤矿企业可加强管理第二、第三类危险源的防范措施。张培森等[9]基于2008—2021年全国煤矿事故数量及死亡人数的统计数据,分别从事故发生地区、事故等级、事故类型及发生时间4个维度分析我国煤矿安全事故,并预测了2022—2023年的百万吨死亡率。程磊等[10]运用数理统计以及系统聚类树分析法,结合Origin和Matlab软件,重点从伤亡人数、类型、时间3个方面分析煤矿事故,并划分了事故类型的风险等级。李敏等[11]研究2000—2021年发生的360起煤矿重特大火灾事故,从时间、地域、地点、煤矿所有制、点火源和外部致灾原因等维度,统计分析了我国煤矿重特大火灾事故一般性特征及致灾原因,发现管理不善是导致重特大火灾事故的主要原因。
上述研究较少采用事故致因模型深入统计分析煤矿事故发生的原因,且提出的对策建议不够系统。鉴于此,笔者分析统计2013—2023年的煤矿重特大事故案例,以期揭示近年来我国煤矿事故特征,找出事故防治重点,提出事故防范对策建议,为推进我国煤炭工业“十四五”规划期间的持续安全发展奠定基础。
基于国家矿山安全监察局、中国煤炭工业年鉴以及国家煤矿安全网公布的煤矿事故数据及事故调查报告等,统计2013—2023年发生的煤矿重特大事故,见表1
2013—2023年煤矿重特大事故发生起数和死亡人数统计如图1图2所示。2013—2017年,重特大事故起数和死亡人数处于较高水平,但整体发展趋势已得到有效遏制,我国煤矿安全生产形势持续好转。究其原因主要为党中央高度重视安全生产工作,在政策法规、监管监察、安全投入和技术水平等方面均有明显提升。2018—2022年,重特大事故起数在年度分布上波动不大,除2019、2020年分别发生了4起、3起重大事故外,其余年度重特大事故起数均为2起,煤矿重大事故起数虽起伏波动,但仍处在一个相对稳定并逐渐好转的状态。2023年发生4起重大事故、1起特大事故,重特大事故有所反弹,说明我国煤矿重特大事故还未得到根本性遏制。特大事故在2013、2016、2023年度时有发生,尤其是2023年2月发生的内蒙古阿拉善盟新井煤业特别重大坍塌事故,造成53人死亡,说明我国煤矿安全生产形势仍然严峻,安全生产任务更加艰巨,需要采取更有力、更科学的措施。
2013—2023年我国发生的煤矿重特大事故发生起数和死亡人数按事故类型统计情况如图3图4 所示。从图中可以看出,瓦斯事故占事故总起数的51%,其次是水灾事故与火灾事故,分别占事故总数的12%和10%。瓦斯、煤尘、水、火和顶板事故发生起数和死亡人数合计占比分别高达87%和86%,说明煤矿5大灾害防治仍是煤矿安全生产工作的重点。坍塌事故发生起数占比3%,但其造成的死亡人数占比达到5%,说明坍塌类事故发生数量不多,但事故所造成的破坏大、伤亡高、后果严重,需要引起重视。
2013—2023年我国发生的煤矿重特大事故按月份统计情况如图5所示。从各季度事故发生情况分析,第4季度事故率较高,共发生21起,占事故总起数的30.43%。从各月份事故发生情况分析,2—4月事故起数和死亡人数相对较多,5—12月事故起数和死亡人数呈现稳步上升的发展态势。分析其原因为:2月、3月、4月是春节后的复工复产月,煤炭企业为确保生产指标而大幅提高生产强度,从而加剧了煤矿安全生产风险隐患的积累,最终演变为煤矿重特大事故频繁发生;6月份事故最低的原因是由于国家开展安全生产活动月和用电需求最小的影响;而8—9月受夏季用电高峰影响,11—12月受冬季供暖影响,煤炭需求量大幅度增加,部分煤炭企业为了追求高利润、高产量而提高生产强度,忽视安全生产工作,致使煤矿重特大事故处于持续频发时期。
2013—2023年我国发生的煤矿重特大事故发生起数和死亡人数按省份统计总体情况如图6图7所示,重特大事故较严重的省份各年度事故起数和死亡人数分布如图8图9所示。可以看出,贵州、黑龙江、山西3省重特大事故发生起数和死亡人数最多,分别占全国的37.68%和33.16%。贵州和黑龙江是我国煤炭重要产区,但其煤炭赋存条件复杂、灾害类型多、生产规模小,且技术装备水平差、智能化程度低,因此煤矿安全生产问题突出。山西是我国煤炭大省,煤炭产量位居全国第一,但也是高瓦斯煤矿和煤与瓦斯突出矿井数量最多的地区之一,瓦斯事故易造成重大人员伤亡和财产损失,因此事故起数和死亡人数位于较多。2023年,贵州山脚树煤矿发生重大火灾事故,黑龙江第4季度连续发生2起重大事故,煤矿安全生产形势不容乐观。此外,2016—2023年,内蒙古共发生2起特大事故,造成85人死亡。内蒙古是我国煤炭的主产区之一,需着重加强安全生产工作,保证煤炭安全供应。
不同事故原因导致重特大事故发生的基本情况如图10图11所示。由图10图11可以看出,绝大多数重特大事故的发生,主要是由人的不安全行为所导致,事故起数占比高达74%,其次是物的危险状态和环境的不安全因素。主要原因为:煤炭行业以人力为主导,一线工人文化程度较低且流动性大,安全意识淡薄,普遍存在侥幸和麻痹心理,从而导致“三违”现象普遍存在。同时员工处在密闭且具有潜在危险的环境中工作,缺乏安全感的工作环境对员工的心理、生理产生负面影响。物的危险状态和环境的不安全因素所占比例较低,主要是因为煤炭企业广泛引进了先进的开采技术和机械化、智能化程度较高的安全生产设备,有效降低了煤矿井下作业的安全风险水平。
发生较多的事故类型及历年发生起数和死亡人数分布情况如图12图13所示。由图12图13可知:近10年煤矿发生的重特大事故主要为瓦斯、水灾、火灾、煤尘和顶板事故,这与煤矿5大灾害相对应。2013—2016年是重特大事故高发期,但事故起数和死亡人数呈逐年下降趋势,其中绝大多数为瓦斯事故;2017—2023年,重特大事故数量处于波动期,瓦斯事故数量显著减少,瓦斯事故得到有效遏制,但顶板、火灾和水灾事故仍时有发生,其他事故防治成绩不理想,说明我国煤矿重特大事故防范治理取得一定成效,但总体安全生产形势依然复杂严峻。
结合事故调查统计分析可知:煤矿绝大多数事故发生的直接原因是人的不安全行为和物的危险状态[12]。人的不安全行为与物的危险状态相比更为复杂,不安全行为的有效控制是改善当前煤矿安全生产严峻形势的重要途径[13]。傅贵等[14]在多米诺骨牌模型和瑞士奶酪模型等基础上,提出了事故致因“2-4”模型(24Model),该模型按照事故发生的过程,将事故的原因分为组织因素和个体因素2个大类;再将组织因素分为安全文化和安全管理体系2个小类,将个体因素分为人的安全能力及人和物的安全动作2个小类。第6版24Model如图14所示。
24Model中事故的直接原因是个体的不安全动作和不安全物态;间接原因为个体的安全知识不足、安全意识不高、安全习惯不佳以及安全心理和安全生理的不良状态等5个方面;根本原因是组织的安全管理体系缺陷;根源原因是组织的安全文化缺陷。
2023年2月22日13时许,新井煤业有限公司露天煤矿发生特别重大坍塌事故,造成53人死亡、6人受伤,直接经济损失20 430.25万元。根据24Model,结合事故调查报告,对该事故致因进行分析,如图15所示。
从不安全动作分析,作业人员未按初步设计施工,随意合并台阶,形成超高超陡边坡。事发时,边坡最大垂直高度315 m,整体边坡角达到39°,局部台阶最大边坡角达到61°,计算边坡稳定系数为0.982,处于不稳定状态。
从不安全物态分析,一是采场未按安全设施设计布置足够的监测点,未形成垂直边坡走向的监测线,无法发挥边坡监测预警系统作用;二是采场底部连续进行高强度剥离采煤,超挖边帮岩体压脚量,致使边坡抗滑力减小、下滑力增加,稳定性持续降低,处于失稳状态;三是剥采作业扰动和越界排土导致边坡断层、节理裂隙发育加剧,不断扩展贯通,岩体的完整性持续被破坏。
从个体能力分析,相关单位长期不开展安全生产教育和培训,从业人员不熟悉有关安全生产规章制度和应急预案,未按要求组织应急演练,导致员工安全知识不足、安全意识不高、安全心理和生理状态不良,且存在侥幸心理、麻痹心理、冒险心理等。相关单位人员违章指挥、冒险作业、越界开采、未按照批准的初步设计和安全专篇组织建设施工。
从管理体系分析,一是安全管理不力,安全生产管理机构存在缺陷,安全生产规章制度存在漏洞,未开展安全生产教育培训和日常应急演练;二是安全监管不实,行政审批层层失守,对越界剥离查处不力,复工验收把关不严,监管监察不实,对重大隐患视而不见;三是应急处置不力,没有制定生产安全事故应急预案,没有明确紧急情况下的撤离顺序和路线,没有组织过应急演练,事故发生后缺乏有组织的人员逃生。
安全发展理念不坚定,安全与发展的统筹关系没理清,重发展轻安全的问题突出,主观认为露天煤矿风险小、灾害轻、不会发生大事故,从而降低安全标准,放松安全管理,为事故发生埋下祸根。企业安全文化未形成,安全生产主体责任严重不落实,盲目要产量、要效益,安全生产费用挪用,违章指挥、冒险作业,对重大安全隐患视而不见。
综上分析,由于组织层面和个体层面存在缺陷形成隐患,加之双重预防机制落实不到位,未能及时从根本上消除事故隐患,最终导致事故发生。因此,煤矿应通过构建安全风险分级管控和隐患排查治理双重预防机制,分析、评估和跟踪每个危险因素的风险态势,确保各项管控措施落实到位,有效管控风险;对于风险管控失效形成的隐患,通过隐患排查治理,消除事故隐患,从源头上保障安全生产。
近年来,煤矿重大灾害治理提速推进,但安全生产形势依然复杂严峻。各级煤矿从业人员要加强思想认识、坚守生命红线,构筑双重机制、筑牢安全防线,坚持常抓不懈、做到久久为功,从安全监管、科技兴安、队伍建设、安全文化[15-18]等方面,切实提升煤矿安全生产水平,有效遏制煤矿重特大事故发生,充分发挥能源供应压舱石作用。
1) 加强监管服务能力提升建设。着力提升政府安全监管服务能力,积极发挥政府部门在安全生产工作中的监管和服务职能,创新体制机制、细化工作措施、改进执法服务方式、提升执法效能,给予煤矿企业实质性的指导和帮助,切实为煤矿解决问题。
2) 推进安全治理模式向事前预防转型。引导煤矿企业树立区域治理、综合治理和超前治理的防灾理念,推进矿山隐蔽致灾因素常态化和制度化普查、治理工作。提升安全风险早期识别和重大灾害监测预警能力,建设事前预防型煤矿安全风险监测预警体系,推进我国矿山安全治理模式向事前预防转型。
1) 加强煤矿安全基础理论研究。加强煤矿安全生产管理体系、煤矿安全事故发生机制、煤矿安全管理效率、煤矿安全生产大数据应用基础等方面的研究。重点研究深部矿井多灾种一体化智能防控理论,煤岩瓦斯复合动力灾害发生机制,煤矿冲击地压主控地质因素及发生机制,矿井内外因火灾风险判识理论与防控方法,复杂地质条件下顶板水害形成机制,大采深矿井煤层底板岩溶发育规律,高地应力及高水压条件下深部煤层底板突水机制,采空区遗煤自燃引爆机制,露天开采与生态环境动态响应耦合机制,露天矿滑坡灾害精准化预警理论,矿井粉尘产生机制,职业危害接触限值与致病机制等。夯实基础,为煤矿安全生产管理和煤矿重大灾害防控提供支撑。
2) 加强基础和关键共性技术研发。重点突破透明地质、井下边缘计算轻量化技术、快速掘进技术、井下人员智能个体防护技术装备、智能通风、重大灾害防治成套智能化技术和装备、露天开采无人化连续作业、煤矿安全风险智能识别与评估、井下数码电子雷管技术、智能视频监察监管执法技术、井下施工远程监控技术等。推动煤炭行业数据标准化进程,加强煤矿场景的人工智能技术研发应用。
3) 推进智能化改造。以数字化、网络化、智能化为方向,探索建立国家级煤矿信息大数据分析与共享交换平台,同步推进网络安全和煤矿智能化发展,加快工业互联网和车联网、新一代通信技术、云计算、大数据、人工智能、虚拟现实等现代信息技术在煤炭工业领域的推广应用,实现装备集中智能控制、系统智能决策、风险智能化评估与预警、安全监管监察规范精准执法、安全培训线上线下一体化。推进煤炭生产企业建立安全、共享、高效的煤矿智能化大数据应用平台,构建实时透明的煤矿地质、智能设计、生产、洗选等数据链条,实现煤矿智能化和大数据的深度融合与应用。
1) 加强外部高素质人才引进。积极引进高学历高素质人才,拓宽外部人才引进通道,提升员工整体素质,建立针对智能化建设、灾害防治、应急管理、安全文化等方面的煤矿专业队伍,配备满足需要的高素质技术及管理人员,保障人才引进所需的资金投入,建立健全人才引进方面的各类规章制度和保障措施。
2) 加强内部人才培养与培训。针对智能化建设、灾害防治、应急管理、安全文化等方面,加强煤矿从业人员培训,建立健全职业发展通道机制,优化知识型、技能型、管理型人才发展体系。加强煤矿智能化复合型人才培养工作,鼓励学科交叉融合,培育一批具备矿业工程、安全工程、信息工程、计算机技术与应用、人工智能等知识技能的煤矿智能化人才队伍。
3) 建立煤矿智能化产业创新联盟。整合社会优质煤矿智能化相关产业资源,以行业协会、高校、研究院所、行业企业、应用矿山等为主体成立智慧矿山产业联盟,组成专业智能化建设科技攻关团队,充分发挥联盟成员在各自专业领域优势,针对煤矿智能化建设需求,提供精准精深服务。
4) 强化国际交流与合作。围绕煤矿智能化前沿新工艺、新技术和新装备,开展跨领域、跨学科、跨专业协同研发合作。加强与“一带一路”沿线国家能源发展战略对接,构建煤矿智能化技术交流共享机制,探索与沿线国家企业、研究机构建立战略合作伙伴关系,深化互信合作,促进互利共赢。以国际合作促进技术交流,带动我国煤矿智能化工艺、技术、装备、标准和服务走出去,同时引入国际煤矿智能化先进技术装备、管理理念、服务模式等,培育具有国际影响力的品牌产品,提升我国煤炭工业开放水平。
1) 以党建为引领,推动安全文化建设。以习近平新时代中国特色社会主义思想为指导,强化党对安全工作的领导,贯彻落实“党政同责、一岗双责、齐抓共管、失职追责”的责任体系,依据“分工协作、条块结合、归口管理”的原则,形成保障安全合力。改进企业安全生产教育方式,以党建宣传、党建学习助力安全生产文化传播,依据安全生产内容加强安全文化教育,充分发挥党支部、团支部、工会等组织力量,开展科普宣传、知识问答、读书竞赛等多样化安全生产教育活动,确保安全文化深入人心。
2) 以班组建设为抓手,加强安全文化建设。班组是企业的细胞,是煤矿安全生产基础工作的源头,是安全文化建设的基本单位。通过规范班组安全文化建设考核制度、定期总结完善班组建设措施、健全完善班组长业绩考核标准、开展多种多样安全文化建设活动等手段,让安全文化以有形、无形的力量影响员工思想,提高员工安全素质。此外,充分利用微信、微博、客户端等移动互联网平台,加强移动互联网、VR技术在安全文化宣传教育领域的应用,广泛宣传报道各地煤矿安全与应急管理动态,普及防灾减灾知识,吸引煤矿从业人员广泛参与煤矿安全建设工作,提高从业人员防灾避险意识和自救互救能力。
3) 构建双重预防体系,有效遏制事故发生。煤矿企业负责人要从落实党政同责、一岗双责的政治高度,推动全员充分认识到当前安全管理工作面临的严峻形势和构建双重预防机制的重要性,切实将风险分级管控和隐患排查治理工作落实到位;重点针对煤矿井下五大灾害及各大生产系统开展风险辨识,应用作业条件危险性评价法、风险矩阵法等确定风险等级,采取教育控制、管理控制、工程控制等针对性地制订相关管控措施,落实风险分级管控;根据风险辨识结果,按照日常排查和定期排查相结合的原则开展隐患排查工作,在实施隐患排查后应在矿区内明显位置公示排查出的隐患,及时更新隐患的排查和治理情况,同时需要组织人员评价整改情况,确保消除事故隐患。
4) 加强社会关注,提高社会认可度。煤炭行业在国民经济中长期发挥着重要的压舱石作用。但一直以来,“煤炭行业是夕阳行业”等成见在公众心中已经根深蒂固,“脏、乱、差、苦、累、险”是人们对煤炭行业比较普遍的印象。近些年来我国煤炭行业机械化、智能化水平在整体上已经有了显著提升,开采技术以及工作环境都有了较大进步和改善。但是现阶段,煤炭行业还是没有被社会普遍认可。因此,应充分利用有影响的传统媒体和互联网新媒体,广泛有针对性地宣传煤矿企业在安全生产、转型发展和企业文化方面的成绩,让社会各界对煤炭行业重新建立“好感”,树立企业良好社会形象,提高社会认可度。
1) 2013—2023年煤矿重特大事故起数和死亡人数呈整体下降趋势,进入“十二五”规划以来我国煤矿安全生产水平明显提高,但2023年发生1起特大事故、4起重大事故,重特大事故反弹明显,说明我国煤矿安全生产形势仍然严峻。
2) 煤矿5大灾害防治仍是煤矿安全生产工作的重点。按照月份分析事故,第4季度是事故高发期;按照事故原因分析,人的不安全行为是导致事故发生的主要原因;通过24Model分析可知:当个体层面和组织层面存在隐患并且双重预防措施不到位时,易导致事故发生。
3) 应从安全监管、科技兴安、队伍建设、安全文化等方面,加强事故防范,切实提升煤矿安全生产水平。
  • 国家自然科学基金资助(52174188)
  • 国家自然科学基金资助(U23B2094)
  • 天地科技公司科技创新创业资金专项项目(2023-TD-MS009)
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2024年第34卷第9期
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doi: 10.16265/j.cnki.issn1003-3033.2024.09.0208
  • 接收时间:2024-03-20
  • 首发时间:2025-07-09
  • 出版时间:2024-09-28
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  • 收稿日期:2024-03-20
  • 修回日期:2024-06-24
基金
国家自然科学基金资助(52174188)
国家自然科学基金资助(U23B2094)
天地科技公司科技创新创业资金专项项目(2023-TD-MS009)
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    煤炭科学研究总院有限公司,北京 100013

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** 刘英杰(1985—),男,内蒙古通辽人,博士,研究员,主要从事煤矿灾害监测预警与防控、应急管理、应急救援技术与装备的研究与开发应用。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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