Article(id=1148106732649312414, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1148106709542892487, articleNumber=1003-3033(2025)04-0165-08, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.04.0474, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732118400000, receivedDateStr=2024-11-21, revisedDate=1739376000000, revisedDateStr=2025-02-13, acceptedDate=null, acceptedDateStr=null, onlineDate=1751659575855, onlineDateStr=2025-07-05, pubDate=1745769600000, pubDateStr=2025-04-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1751659575855, onlineIssueDateStr=2025-07-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1751659575855, creator=13701087609, updateTime=1751659575855, updator=13701087609, issue=Issue{id=1148106709542892487, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='4', pageStart='1', pageEnd='264', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=0, createTime=1751659570346, creator=13701087609, updateTime=1757560692417, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1172857809499730113, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1148106709542892487, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1172857809499730114, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1148106709542892487, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=165, endPage=172, ext={EN=ArticleExt(id=1149758075973845017, articleId=1148106732649312414, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Downward layered mining based on G1-RF combined empowerment cloud model evaluation of filling stability, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

In order to solve the index ambiguity problem in the risk assessment process of downward layered mining filling body stability,the filling body stability assessment model was constructed. Firstly,12 factors affecting the stability of the filling body,such as cohesion,exposed area,stress ratio,etc.,were selected as risk evaluation indicators to establish the evaluation index system. Secondly,the cloud model theory was introduced to calculate the cloud digital characteristics of each indicator,and the comprehensive weight was obtained by using G1-RF,and a comprehensive evaluation model of the stability of layered mining filler was constructed based on the G1-RF combined empowerment cloud model to determine the stability risk level of the mine filler. Finally,the evaluation method was applied to the stability analysis of the mine filler in the actual project. The results show that the comprehensive evaluation method can effectively solve the problems of indicator ambiguity and weak relevance in the process of risk assessment,more accurately and quickly evaluate the stability of the filling body,and realize the visualization of the risk level.

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为解决下向分层开采充填体稳定性风险评估过程中指标模糊性问题,构建充填体稳定性评估模型。首先,选取充填体黏聚力、暴露面积、应力比等12项充填体稳定性影响因素作为风险评价指标,建立评价指标体系;其次,引入云模型理论计算各指标云数字特征,利用序关系分析(G1)-随机森林(RF)博弈论组合赋权法获取综合权重,构建基于G1-RF博弈论组合赋权云模型的下向分层开采充填体稳定性综合评价模型,确定矿山充填体稳定性风险等级;最后,将该评价方法应用于实际工程中矿山充填体稳定性分析。结果表明:采用该综合评价方法,能够有效解决风险评估过程中指标模糊性与弱关联性问题,更准确快速地评价充填体的稳定性,并且实现风险等级的可视化。

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何玉珍 (2000—),女,甘肃武威人,硕士研究生,研究方向为金属矿山地下开采地压灾害监测与风险评估。E-mail:

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何玉珍 (2000—),女,甘肃武威人,硕士研究生,研究方向为金属矿山地下开采地压灾害监测与风险评估。E-mail:

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何玉珍 (2000—),女,甘肃武威人,硕士研究生,研究方向为金属矿山地下开采地压灾害监测与风险评估。E-mail:

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Applied Sciences, 2023, 13(15): DOI:10.3390/app13158688., articleTitle=Research on optimization and numerical simulation of layout scheme of mining approach in downward slicing and filling method, refAbstract=null), Reference(id=1165197858769740494, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=3, pageStart=143, pageEnd=148, url=null, language=null, rfNumber=[21], rfOrder=36, authorNames=黄灏, 乔登攀, journalName=采矿技术, refType=null, unstructuredReference=黄灏, 乔登攀. 毛坪铅锌矿下向水平分层充填体布筋优化研究[J]. 采矿技术, 2023, 23(3):143-148., articleTitle=毛坪铅锌矿下向水平分层充填体布筋优化研究, refAbstract=null)], funds=[Fund(id=1165197856412541587, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, awardId=51974206, language=CN, fundingSource=国家自然科学基金资助(51974206), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1165197852771885620, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, xref=1, ext=[AuthorCompanyExt(id=1165197852784468533, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, companyId=1165197852771885620, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 School of Resources and Environmental Engineering,Wuhan University of Science and Technology,Wuhan Hubei 430081,China), AuthorCompanyExt(id=1165197852792857142, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, companyId=1165197852771885620, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 武汉科技大学 资源与环境工程学院,湖北 武汉 430081)]), AuthorCompany(id=1165197852876743224, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, xref=2, ext=[AuthorCompanyExt(id=1165197852885131833, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, companyId=1165197852876743224, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 No.2 Mine Area,Jinchuan Group Nickel and Cobalt Co.,Ltd.,Jinchang Gansu 737100,China), AuthorCompanyExt(id=1165197852889326138, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, companyId=1165197852876743224, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 金川集团镍钴有限公司 二矿区,甘肃 金昌 737100)])], figs=[ArticleFig(id=1165197854508327533, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Fig.1, caption=Cloud model for evaluating grades of filling body risk indicators, figureFileSmall=mpLrHnEq1oH8IOcTZV8x8Q==, figureFileBig=w35LEs2+hUvlAvd+8o9OUg==, tableContent=null), ArticleFig(id=1165197854634156656, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=图1, caption=充填体风险指标评价等级云模型, figureFileSmall=mpLrHnEq1oH8IOcTZV8x8Q==, figureFileBig=w35LEs2+hUvlAvd+8o9OUg==, tableContent=null), ArticleFig(id=1165197854718042736, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 1, caption=

Description of stability index of filling body

, figureFileSmall=null, figureFileBig=null, tableContent=
指标名称 指标说明
矿体埋
X1
充填体随埋深增加更易发生变形或沉降。目前埋深等级分类标准相关研究较少,而地应力等级在一定程度上可表征埋深等级[12],进一步得出风险等级为Ⅰ级、Ⅱ级、Ⅲ级、Ⅳ级对应的埋深范围以次为:低于300、300 ~ 600、600 ~ 2 000 m,高于2 000 m
矿体倾
X2
一般来说矿体倾角越小,充填体稳定性越高。矿体倾角的分类通常采用几何学和地质学原理,将矿体按照倾斜角度分为平缓倾斜、中等倾斜、陡峭倾斜和极陡倾斜4个等级[8]
地下水条
X3
充填体中的水分既减小其之间的黏聚力又降低剪切强度;同时地下水中溶解物质不仅对充填体造成溶解作用,还降低其强度
围岩稳定
X4
围岩对充填体有一定局部支撑作用,不仅可以承载充填体本身重力,而且可以降低承载层上的力,使充填体更稳定
充填体黏
聚力X5
充填体内部颗粒之间存在相互吸引力或黏结力,高黏聚力使充填体颗粒之间相互作用更强,从而提高充填体整体强度不易于被破坏[13]
充填体密
X6
当向充填体施加更大垂直应力时,可以增加充填体密实度和抗压强度。在水化反应过程中,大量自由水会被消耗掉,而且随着反应强度增加,充填体密度增大,其稳定性也提高[914]
充填体暴
露面积X7
骨料中值粒径指充填材料中颗粒尺寸分布中的中间值,骨料粒径越小,充填体暴露面积越大,不仅更易受到自然力侵蚀,而且受到顶板剪切力应力作用越明显,充填体越不稳定[9]
垂直应力与
水平应力比X8
提高其整体稳定性;增加水平应力可以提高充填体的整体强度,减少水平变形和开裂。因此二者比值越小,对充填体稳定性更有益[9]
骨料中值
粒径X9
充填体中水分会使其之间黏聚力减小,导致充填体剪切强度降低;充填体会更加密实,变形幅度会越小,抗压强度越好,也会减小充填体渗透性[3]
充填体抗
压强度X10
抗压强度是反映充填体稳定性的重要力学性质,高抗压强度意味着充填体能够更好承受来自底层和上覆岩层的垂直应力,从而减小充填体发生沉降和变形的可能性[15]
充填体接
顶效果X11
充填体与上部岩层或底层接触关系直接影响着充填体承载强度,充填体接顶效果越好,充填体稳定性越高[9]
爆破扰动X12 爆破扰动会引起地下振动,导致充填体松动或产生裂隙,从而减弱其支撑作用。爆破扰动根据岩爆烈度所对应的4个等级所产生的灾害影响大小转换为爆破扰动定性分级[3]
), ArticleFig(id=1165197854793540210, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表1, caption=

充填体稳定性评估指标说明

, figureFileSmall=null, figureFileBig=null, tableContent=
指标名称 指标说明
矿体埋
X1
充填体随埋深增加更易发生变形或沉降。目前埋深等级分类标准相关研究较少,而地应力等级在一定程度上可表征埋深等级[12],进一步得出风险等级为Ⅰ级、Ⅱ级、Ⅲ级、Ⅳ级对应的埋深范围以次为:低于300、300 ~ 600、600 ~ 2 000 m,高于2 000 m
矿体倾
X2
一般来说矿体倾角越小,充填体稳定性越高。矿体倾角的分类通常采用几何学和地质学原理,将矿体按照倾斜角度分为平缓倾斜、中等倾斜、陡峭倾斜和极陡倾斜4个等级[8]
地下水条
X3
充填体中的水分既减小其之间的黏聚力又降低剪切强度;同时地下水中溶解物质不仅对充填体造成溶解作用,还降低其强度
围岩稳定
X4
围岩对充填体有一定局部支撑作用,不仅可以承载充填体本身重力,而且可以降低承载层上的力,使充填体更稳定
充填体黏
聚力X5
充填体内部颗粒之间存在相互吸引力或黏结力,高黏聚力使充填体颗粒之间相互作用更强,从而提高充填体整体强度不易于被破坏[13]
充填体密
X6
当向充填体施加更大垂直应力时,可以增加充填体密实度和抗压强度。在水化反应过程中,大量自由水会被消耗掉,而且随着反应强度增加,充填体密度增大,其稳定性也提高[914]
充填体暴
露面积X7
骨料中值粒径指充填材料中颗粒尺寸分布中的中间值,骨料粒径越小,充填体暴露面积越大,不仅更易受到自然力侵蚀,而且受到顶板剪切力应力作用越明显,充填体越不稳定[9]
垂直应力与
水平应力比X8
提高其整体稳定性;增加水平应力可以提高充填体的整体强度,减少水平变形和开裂。因此二者比值越小,对充填体稳定性更有益[9]
骨料中值
粒径X9
充填体中水分会使其之间黏聚力减小,导致充填体剪切强度降低;充填体会更加密实,变形幅度会越小,抗压强度越好,也会减小充填体渗透性[3]
充填体抗
压强度X10
抗压强度是反映充填体稳定性的重要力学性质,高抗压强度意味着充填体能够更好承受来自底层和上覆岩层的垂直应力,从而减小充填体发生沉降和变形的可能性[15]
充填体接
顶效果X11
充填体与上部岩层或底层接触关系直接影响着充填体承载强度,充填体接顶效果越好,充填体稳定性越高[9]
爆破扰动X12 爆破扰动会引起地下振动,导致充填体松动或产生裂隙,从而减弱其支撑作用。爆破扰动根据岩爆烈度所对应的4个等级所产生的灾害影响大小转换为爆破扰动定性分级[3]
), ArticleFig(id=1165197854869037684, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 2, caption=

Quantitative indicator classification criteria for stability assessment of filling body

, figureFileSmall=null, figureFileBig=null, tableContent=
风险
等级
X1/km X2/(°) X5/MPa X6/(g·cm-3) X7/m2 X8 X9/μm X10/MPa
<0.3 <10 ≥0.2 ≥2.5 <150 <1.2 <40 ≥2.0
[0.3,0.6) [10,30) [0.15,0.2) [1.6,2.5) [150,250) [1.2,1.8) [40,70) [1.5,2.0)
[0.6,2) [30,60) [0.10,0.15) [1.2,1.6) [250,350) [1.8,2.4) [70,100) [1.0,1.5)
≥2 ≥60 <0.1 <1.2 ≥350 ≥2.4 ≥100 <1.0
), ArticleFig(id=1165197854969700982, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表2, caption=

充填体稳定性评估定量指标分类标准

, figureFileSmall=null, figureFileBig=null, tableContent=
风险
等级
X1/km X2/(°) X5/MPa X6/(g·cm-3) X7/m2 X8 X9/μm X10/MPa
<0.3 <10 ≥0.2 ≥2.5 <150 <1.2 <40 ≥2.0
[0.3,0.6) [10,30) [0.15,0.2) [1.6,2.5) [150,250) [1.2,1.8) [40,70) [1.5,2.0)
[0.6,2) [30,60) [0.10,0.15) [1.2,1.6) [250,350) [1.8,2.4) [70,100) [1.0,1.5)
≥2 ≥60 <0.1 <1.2 ≥350 ≥2.4 ≥100 <1.0
), ArticleFig(id=1165197855041004152, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 3, caption=

Qualitative indicator classification criteria for stability assessment of filling body

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风险等级 X3 X4 X11 X12 赋值
不出现透水现象,围岩干燥 围岩坚固,稳定性高 料浆均匀稳定,接顶效果好 无明显影响,充填无变形、裂缝等 0~2
岩体受地下水影响较小 节理发育,岩质较硬 料浆沉降率小,大部分接顶 引起充填体轻微变形或裂缝 2~4
围岩岩体受地下水影响比较大 节理发育明显,岩石质地较软 料浆分层离析明显,少部分接顶 引起较明显的变形、裂缝或局部坍塌 4~6
地下水发育明显,岩体长期含水 岩体破碎 料浆分层严重,未接顶 导致充填体严重破坏,大范围坍塌失稳 6~8
), ArticleFig(id=1165197855137473146, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表3, caption=

充填体稳定性评估定性指标评分标准

, figureFileSmall=null, figureFileBig=null, tableContent=
风险等级 X3 X4 X11 X12 赋值
不出现透水现象,围岩干燥 围岩坚固,稳定性高 料浆均匀稳定,接顶效果好 无明显影响,充填无变形、裂缝等 0~2
岩体受地下水影响较小 节理发育,岩质较硬 料浆沉降率小,大部分接顶 引起充填体轻微变形或裂缝 2~4
围岩岩体受地下水影响比较大 节理发育明显,岩石质地较软 料浆分层离析明显,少部分接顶 引起较明显的变形、裂缝或局部坍塌 4~6
地下水发育明显,岩体长期含水 岩体破碎 料浆分层严重,未接顶 导致充填体严重破坏,大范围坍塌失稳 6~8
), ArticleFig(id=1165197855221359227, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 4, caption=

Cloud digital characteristics of stability indicators of filling bodies under different grades

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评价指标 (HeExEn)
Ⅰ级 Ⅱ级 Ⅲ级 Ⅳ级
X1 (0.05,0.15,0.05) (0.05,0.45,0.05) (0.05,1.30,0.23) (0.05,2.00,0.23)
X2 (0.05,5.00,1.67) (0.05,20.00,3.33) (0.05,45.00,5.00) (0.05,60.00,5.00)
X3 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
X4 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
X5 (0.05,0.20,0.01) (0.05,0.18,0.01) (0.05,0.13,0.01) (0.05,0.05,0.02)
X6 (0.05,2.50,0.15) (0.05,2.05,0.15) (0.05,1.40,0.07) (0.05,0.60,0.20)
X7 (0.05,75.00,25.00) (0.05,225.00,25.00) (0.05,375.00,25.00) (0.05,450.00,25.00)
X8 (0.05,0.60,0.20) (0.05,1.50,0.10) (0.05,2.10,0.10) (0.05,2.70,0.10)
X9 (0.05,20.00,6.67) (0.05,55.00,5.00) (0.05,85.00,5.00) (0.05,100.00,5.00)
X10 (0.05,2.00,0.08) (0.05,1.75,0.08) (0.05,1.25,0.08) (0.05,0.50,0.17)
X11 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
X12 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
), ArticleFig(id=1165197855292662397, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表4, caption=

不同等级下充填体稳定性指标的云数字特征

, figureFileSmall=null, figureFileBig=null, tableContent=
评价指标 (HeExEn)
Ⅰ级 Ⅱ级 Ⅲ级 Ⅳ级
X1 (0.05,0.15,0.05) (0.05,0.45,0.05) (0.05,1.30,0.23) (0.05,2.00,0.23)
X2 (0.05,5.00,1.67) (0.05,20.00,3.33) (0.05,45.00,5.00) (0.05,60.00,5.00)
X3 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
X4 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
X5 (0.05,0.20,0.01) (0.05,0.18,0.01) (0.05,0.13,0.01) (0.05,0.05,0.02)
X6 (0.05,2.50,0.15) (0.05,2.05,0.15) (0.05,1.40,0.07) (0.05,0.60,0.20)
X7 (0.05,75.00,25.00) (0.05,225.00,25.00) (0.05,375.00,25.00) (0.05,450.00,25.00)
X8 (0.05,0.60,0.20) (0.05,1.50,0.10) (0.05,2.10,0.10) (0.05,2.70,0.10)
X9 (0.05,20.00,6.67) (0.05,55.00,5.00) (0.05,85.00,5.00) (0.05,100.00,5.00)
X10 (0.05,2.00,0.08) (0.05,1.75,0.08) (0.05,1.25,0.08) (0.05,0.50,0.17)
X11 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
X12 (0.05,1.00,0.33) (0.05,3.00,0.33) (0.05,5.00,0.33) (0.05,7.00,0.33)
), ArticleFig(id=1165197855372354175, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 5, caption=

Training sample data

, figureFileSmall=null, figureFileBig=null, tableContent=
矿山 X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 目标值
S1 0.87 70 2.8 4.8 0.096 1.56 120 2.76 165 3.40 4.3 4.4 0.666
S2 0.91 75 4.4 4.2 0.590 2.06 210 1.50 155 4.50 4.6 4.7 0.618
S3 1.10 67 3.2 5.0 0.750 2.70 312 1.61 178 6.40 4.0 4.2 0.659
S4 0.53 79 4.5 6.6 0.530 3.10 237 1.59 172 5.10 3.9 4.5 0.637
S5 0.48 65 5.4 4.6 0.720 1.60 150 0.96 163 3.50 4.2 3.5 0.492
S6 0.62 35 4.0 5.8 0.220 2.61 175 2.89 150 3.32 3.7 6.2 0.683
), ArticleFig(id=1165197855468823169, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表5, caption=

训练样本数据

, figureFileSmall=null, figureFileBig=null, tableContent=
矿山 X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 目标值
S1 0.87 70 2.8 4.8 0.096 1.56 120 2.76 165 3.40 4.3 4.4 0.666
S2 0.91 75 4.4 4.2 0.590 2.06 210 1.50 155 4.50 4.6 4.7 0.618
S3 1.10 67 3.2 5.0 0.750 2.70 312 1.61 178 6.40 4.0 4.2 0.659
S4 0.53 79 4.5 6.6 0.530 3.10 237 1.59 172 5.10 3.9 4.5 0.637
S5 0.48 65 5.4 4.6 0.720 1.60 150 0.96 163 3.50 4.2 3.5 0.492
S6 0.62 35 4.0 5.8 0.220 2.61 175 2.89 150 3.32 3.7 6.2 0.683
), ArticleFig(id=1165197855590457987, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 6, caption=

Subjective weights of indicators determined by G1 method

, figureFileSmall=null, figureFileBig=null, tableContent=
W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11 W12
0.020 4 0.043 5 0.016 9 0.096 3 0.217 7 0.016 1 0.131 5 0.063 3 0.032 1 0.026 4 0.050 6 0.285 2
), ArticleFig(id=1165197855703704197, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表6, caption=

G1法确定的各指标主观权重

, figureFileSmall=null, figureFileBig=null, tableContent=
W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11 W12
0.020 4 0.043 5 0.016 9 0.096 3 0.217 7 0.016 1 0.131 5 0.063 3 0.032 1 0.026 4 0.050 6 0.285 2
), ArticleFig(id=1165197855888253575, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 7, caption=

Objective weights of indicators determined by RF methodology

, figureFileSmall=null, figureFileBig=null, tableContent=
w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12
0.034 6 0.034 7 0.030 4 0.170 8 0.260 4 0.048 7 0.024 7 0.178 5 0.010 6 0.150 9 0.035 0 0.020 7
), ArticleFig(id=1165197855942779529, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表7, caption=

RF法确定的各指标客观权重

, figureFileSmall=null, figureFileBig=null, tableContent=
w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12
0.034 6 0.034 7 0.030 4 0.170 8 0.260 4 0.048 7 0.024 7 0.178 5 0.010 6 0.150 9 0.035 0 0.020 7
), ArticleFig(id=1165197856005694091, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 8, caption=

Combined weights of indicators

, figureFileSmall=null, figureFileBig=null, tableContent=
W 1 * W 2 * W 3 * W 4 * W 5 * W 6 * W 7 * W 8 * W 9 * W 10 * W 11 * W 12 *
0.027 3 0.039 4 0.023 5 0.132 0 0.238 3 0.031 8 0.081 0 0.117 3 0.021 8 0.086 1 0.043 1 0.158 4
), ArticleFig(id=1165197856064414349, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表8, caption=

各指标的综合权重

, figureFileSmall=null, figureFileBig=null, tableContent=
W 1 * W 2 * W 3 * W 4 * W 5 * W 6 * W 7 * W 8 * W 9 * W 10 * W 11 * W 12 *
0.027 3 0.039 4 0.023 5 0.132 0 0.238 3 0.031 8 0.081 0 0.117 3 0.021 8 0.086 1 0.043 1 0.158 4
), ArticleFig(id=1165197856135717519, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=EN, label=Table 9, caption=

Evaluation results and comparison of filling body stability grade

, figureFileSmall=null, figureFileBig=null, tableContent=
评价对象 综合隶属度 云模型评价
结果
CRITIC-G1
法评价结果
模糊数学
理论模型
金川三矿 0.208 2 0.308 6 0.255 1 0.228 1
武山铜矿 0.222 9 0.236 3 0.318 7 0.222 1
前河金矿 0.175 2 0.265 4 0.287 7 0.271 7
), ArticleFig(id=1165197856215409297, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1148106732649312414, language=CN, label=表9, caption=

充填体稳定性等级评价结果及对比

, figureFileSmall=null, figureFileBig=null, tableContent=
评价对象 综合隶属度 云模型评价
结果
CRITIC-G1
法评价结果
模糊数学
理论模型
金川三矿 0.208 2 0.308 6 0.255 1 0.228 1
武山铜矿 0.222 9 0.236 3 0.318 7 0.222 1
前河金矿 0.175 2 0.265 4 0.287 7 0.271 7
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基于G1-RF组合赋权云模型的下向分层开采充填体稳定性评价
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何玉珍 1 , 王文杰 教授 1 , 陈仲杰 高级工程师 2
中国安全科学学报 | 安全工程技术 2025,35(4): 165-172
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中国安全科学学报 | 安全工程技术 2025, 35(4): 165-172
基于G1-RF组合赋权云模型的下向分层开采充填体稳定性评价
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何玉珍1 , 王文杰 教授1, 陈仲杰 高级工程师2
作者信息
  • 1 武汉科技大学 资源与环境工程学院,湖北 武汉 430081
  • 2 金川集团镍钴有限公司 二矿区,甘肃 金昌 737100
  • 何玉珍 (2000—),女,甘肃武威人,硕士研究生,研究方向为金属矿山地下开采地压灾害监测与风险评估。E-mail:

Downward layered mining based on G1-RF combined empowerment cloud model evaluation of filling stability
Yuzhen HE1 , Wenjie WANG1, Zhongjie CHEN2
Affiliations
  • 1 School of Resources and Environmental Engineering,Wuhan University of Science and Technology,Wuhan Hubei 430081,China
  • 2 No.2 Mine Area,Jinchuan Group Nickel and Cobalt Co.,Ltd.,Jinchang Gansu 737100,China
出版时间: 2025-04-28 doi: 10.16265/j.cnki.issn1003-3033.2025.04.0474
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为解决下向分层开采充填体稳定性风险评估过程中指标模糊性问题,构建充填体稳定性评估模型。首先,选取充填体黏聚力、暴露面积、应力比等12项充填体稳定性影响因素作为风险评价指标,建立评价指标体系;其次,引入云模型理论计算各指标云数字特征,利用序关系分析(G1)-随机森林(RF)博弈论组合赋权法获取综合权重,构建基于G1-RF博弈论组合赋权云模型的下向分层开采充填体稳定性综合评价模型,确定矿山充填体稳定性风险等级;最后,将该评价方法应用于实际工程中矿山充填体稳定性分析。结果表明:采用该综合评价方法,能够有效解决风险评估过程中指标模糊性与弱关联性问题,更准确快速地评价充填体的稳定性,并且实现风险等级的可视化。

序关系分析法(G1)  /  随机森林(RF)  /  组合赋权  /  云模型  /  下向分层开采  /  充填体稳定性

In order to solve the index ambiguity problem in the risk assessment process of downward layered mining filling body stability,the filling body stability assessment model was constructed. Firstly,12 factors affecting the stability of the filling body,such as cohesion,exposed area,stress ratio,etc.,were selected as risk evaluation indicators to establish the evaluation index system. Secondly,the cloud model theory was introduced to calculate the cloud digital characteristics of each indicator,and the comprehensive weight was obtained by using G1-RF,and a comprehensive evaluation model of the stability of layered mining filler was constructed based on the G1-RF combined empowerment cloud model to determine the stability risk level of the mine filler. Finally,the evaluation method was applied to the stability analysis of the mine filler in the actual project. The results show that the comprehensive evaluation method can effectively solve the problems of indicator ambiguity and weak relevance in the process of risk assessment,more accurately and quickly evaluate the stability of the filling body,and realize the visualization of the risk level.

order relationship analysis method (G1)  /  random forest(RF)  /  portfolio empowerment  /  cloud model  /  downward layered mining  /  stability of the filling body
何玉珍, 王文杰 教授, 陈仲杰 高级工程师. 基于G1-RF组合赋权云模型的下向分层开采充填体稳定性评价. 中国安全科学学报, 2025 , 35 (4) : 165 -172 . DOI: 10.16265/j.cnki.issn1003-3033.2025.04.0474
Yuzhen HE, Wenjie WANG, Zhongjie CHEN. Downward layered mining based on G1-RF combined empowerment cloud model evaluation of filling stability[J]. China Safety Science Journal, 2025 , 35 (4) : 165 -172 . DOI: 10.16265/j.cnki.issn1003-3033.2025.04.0474
充填体在矿山开采过程中对于保障矿山安全生产起着至关重要的作用,充填体稳定性受定量和定性因素共同影响,且各影响因素互有关联、交叉,诸如充填体自身条件、围岩稳固和暴露面积等因素都会影响充填体稳定性,从而对开采工作和生命安全产生隐患[1]。因此,科学准确地判断充填体稳定性,对及时制定充填体失稳应急预案、确保采场施工安全具有重要意义。
目前,国内外对于充填体稳定性评价的研究主要集中于多因素相互耦合作用,通过综合评价模型表征充填体稳定性[2]。李夕兵等[3]根据影响充填体稳定性的5个因素建立煤矿充填系统评价指标体系,构建基于层次模糊综合方法的充填体稳定性评价方法。王石等[4]将层次分析法引入系统动力学模型,预测充填体稳定性。史俊伟等[5]将灰色关联分析法和集对分析法相结合,构建灰色关联-集对分析耦合评判模型评估某矿充填系统稳定性等级。黄旭等[6]构建序关系分析法(Order Relationship Analysis Method,G1)和云化物元模型来确定大冶铁矿充填体稳定性等级。上述研究方法大多采用单一赋权,与组合赋权法相比,评价结果存在合理性较弱等问题。
为此,根据下向分层开采充填体在稳定性风险评估过程中出现的模糊性和弱相关性等问题,结合G1-随机森林(Random Forest,RF)博弈论组合赋权法确定组合权重,从主客观两方面综合考虑各因素的复杂性及相关性,同时,通过正向云发生器实现的云模型,获取指标不同风险等级的综合确定度,以期综合判断充填体稳定性状态,进而提高下向分层开采安全水平。
综合考虑矿山地质条件[7]、充填体特性[8]和开采扰动[1]等对充填体稳定性的影响,选取12个充填体稳定性评价指标,见表1。其中,X1X2X5~X10作为定量指标,直接影响充填体的物理力学性质,具备直接量化计算能力,具体定量指标分级标准见表2。而X3X4X11X12作为与结构设计相关的定性指标,参考工程实际材料及文献[69-11]进行二次处理,使其具备量化计算能力,具体定性指标分级赋值见表3
云模型[16]可解决定性概念和定量描述的不确定转换问题,其核心是用数字特征(期望值Ex、熵En和超熵He)来描述不确定性与模糊性,通过建立隶属函数、云函数和云生成算法,更好地体现复杂系统特征。各指标云模型数字特征参数计算式为:
E x = ( C m i n + C m a x ) / 2 E n = ( C m a x - C m i n ) / 6 H e = k
式中:CminCmax分别为某一指标分级标准的最小值、最大值;k为常数。
根据指标的模糊性程度进行调整,因He增大,En误差值也会随之增大,云层厚度也越大,所以其值不宜过大,此处取0.05。
表2表3的数据代入式(1)中,算出HeExEn,各评价指标云数字特征计算结果见表4
运用正向云发生器,针对表4中云数字特征运用Python生成指标云图,如图1所示。
图1a图1d图1g图1i图1k图1l中,风险等级顺序从左至右均为Ⅰ级、Ⅱ级、Ⅲ级、Ⅳ级,而图1e图1f图1j则相反。可以看出,数据交叉现象相较其他因素更为明显,表明该因素体现出云滴离散性较大,指标取值转化为所隶属风险等级确定度过程中存在模糊性与不确定性。
G1法可降低对评估者主观需求,本文采用该方法进行主观赋权。
RF法可以有效防止过拟合,它有着高准确性、处理大规模数据、提高算法的精确的优点。遍历整个RF训练集D=(xij)mn,得到指标变量xj对所有决策树的影响程度 { η 1 j η 2 j η m j },则该指标变量对RF的整体影响程度为:
η j = 1 m k = 1 m η k j
式中:xij为第i个实例的第j个指标值;m为生成的样本子集。
分别令 j = 1,2 n,重复以上步骤,得到各指标变量对RF的影响程度 { η 1 η 2 η n }。RF根据指标变量对RF的影响程度描述指标变量的重要性,因此,基于RF的指标重要性分数可以表示如下[17]
w j = η j j = 1 n η j
式中:wj为第j个指标的重要性分数;ηj为第j个指标的影响程度。
因为G1法和RF法在计算主客观权重时均存在各自的不足之处,所以在综合考虑主、客观赋权的情况下,采用博弈论组合赋权法,使得二者之间的偏差最小化,以此来提高所得权重的合理性与可靠性,最后得到最优权重组合。
确定博弈论组合赋权权重W*为:
W i * = a 1 * w 1 + a 2 * w 2
式中 a 1 * a 2 *分别为主、客观权重的线性系数归一化处理所得值。
下向分层开采充填体评价是以工程实际为基础,通过指标定量分级及定性分级赋值方法对各评价指标进行风险分级并构建下向分层开采充填体评价指标体系,并划分下向分层开采充填体稳定性风险等级:Ⅰ级(风险较小)、Ⅱ级(风险一般)、Ⅲ级(风险较大)、Ⅳ级(风险极大)。
基于云模型理论,计算不同风险等级下各指标云数字特征。根据矿山实际情况,开展各指标对于指标等级的确定度,结合指标权重计算获得综合确定度,依照最大隶属度原则,确定充填体稳定性等级。综合隶属度计算公式为:
μ ( x ) = e x p - ( x i - E x ) 2 2 ( E n ) 2 W ( θ ) = i = 1 n [ W i * × μ ( x ) ]
式中:μ(x)为确定度;xi为实际指标参数。
以山东招远灵山金矿S1、云南毛坪铅锌矿S2、安徽黄狮涝金矿S3、山东马庄铁矿S4、甘肃金川二矿S5、浙江璜山金矿S6作为训练样本进行模型训练,并以采用下向分层充填开采法的金川三矿、武山铜矿、前河金矿为研究对象,验证G1-RF博弈论组合赋权云模型的有效性及准确性。
查阅文献[18-21],收集S1S2S3S4S5S6等6座矿山相关评价指标数据作为评价模型训练样本,见表5
利用G1法、RF法以及博弈论综合权重法计算出表5中各指标主、客观权重和综合权重,分别见表6表8
文中模型对甘肃金川三矿、江西武山铜矿、河南前河金矿的评价结果与复杂信息下的指标客观权重计算法(Criteria Importance Through Intercriteria Correlation,CRITIC)-G1法评价结果、模糊数学理论模型评价结果对比见表9
可以看出,金川三矿、武山铜矿、前河金矿充填体稳定性风险等级分别为Ⅱ、Ⅲ、Ⅲ级。比较金川三矿与武山铜矿综合隶属度,可知:矿山充填体稳定性风险等级具有较强可靠性。前河金矿稳定性风险等级隶属度相比于Ⅱ级和Ⅳ级综合隶属度较为接近,表明前河金矿需查找影响充填体稳定性最主要因素,通过调节其指标因素可以实现矿山充填体稳定性风险等级有效控制。由表9可知:文中构建的G1-RF博弈论组合赋权云模型能够提高指标关联性和解决模糊性,并实现指标等级可视化,避免因各因素的随机性。RF计算客观权重过程中对异常值敏感,可规避因个别异常数据而导致结果出现较大偏差。文中模型与CRITIC-G1法和模糊数学理论模型得到的结果一致,且三座矿山在实际生产过程中充填体的稳定性与评价结果高度一致,证明该方法对下向分层开采充填体稳定性进行评价的有效可行。
1) G1-RF博弈论组合赋权云模型方法引入云模型理论,在提高指标关联性和解决模糊性的同时,有助于实现指标等级的可视化,避免各因素的随机性,同时,在计算过程中通过机器算法对异常值敏感的特点,可提高计算过程快速性和准确性,有效评估指标信息量及相关性。
2) 将G1-RF博弈论组合赋权云模型方法应用于金川三矿、武山铜矿及前河金矿,得到矿山充填体稳定性风险等级分别为Ⅱ级、Ⅲ级、Ⅲ级。与CRITIC-G1法、模糊数学理论模型评价结果相比,两者结果具有高度一致性,证明该方法在处理相关问题时具有科学性和有效性。
  • 国家自然科学基金资助(51974206)
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2025年第35卷第4期
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doi: 10.16265/j.cnki.issn1003-3033.2025.04.0474
  • 接收时间:2024-11-21
  • 首发时间:2025-07-05
  • 出版时间:2025-04-28
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  • 收稿日期:2024-11-21
  • 修回日期:2025-02-13
基金
国家自然科学基金资助(51974206)
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    1 武汉科技大学 资源与环境工程学院,湖北 武汉 430081
    2 金川集团镍钴有限公司 二矿区,甘肃 金昌 737100
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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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