Article(id=1149738775342919919, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149738762382524507, articleNumber=1003-3033(2024)07-0053-10, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.07.1892, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1704902400000, receivedDateStr=2024-01-11, revisedDate=1712937600000, revisedDateStr=2024-04-13, acceptedDate=null, acceptedDateStr=null, onlineDate=1752048685155, onlineDateStr=2025-07-09, pubDate=1722096000000, pubDateStr=2024-07-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752048685155, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752048685155, creator=13701087609, updateTime=1752048685155, updator=13701087609, issue=Issue{id=1149738762382524507, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='7', 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=1752048682065, creator=13701087609, updateTime=1757316437713, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1171833331021824745, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149738762382524507, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1171833331021824746, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149738762382524507, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=53, endPage=62, ext={EN=ArticleExt(id=1149738775565218032, articleId=1149738775342919919, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Tailings accumulation dam safety state analysis by integrating heterogeneous hierarchical graph, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

In order to investigate the influence of internal and external factors on the safety state of the tailings dam,a method for analysing the safety state of the tailings dam based on heterogeneous hierarchical diagrams was proposed. Firstly,a hierarchical causal graph was constructed based on a priori knowledge to link key factors such as environment,seepage field and stress field with the safety status of tailing dams,and an evaluation index system was established by combining the attribute characteristics of heterogeneous nodes. Secondly,the cloud model and set-pair analysis theory were used to quantitatively calculate the potential logical relationship between the heterogeneous causal graph and the safety stability of the tailings dam. A dynamic interval calculation method for quantitative indicators and a safety status level calculation model were proposed to convert the fuzziness and uncertainty of complex and diverse evaluation indicators into quantitative expressions. Finally,a tailings dam in Luoyang was used as an example to verify the scientificity of the model.The results show that the model can quantitatively analyse the link between factors and states and identify the causes of negative changes in stacked dams. The conclusions of the model analysis can be used for the safety management of the dam-building process.

, correspAuthors=Simiao HAN, 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=Shunling RUAN, Simiao HAN, Yihan YIN, Di LIU, Jiajia LIU, Song JIANG), CN=ArticleExt(id=1149738787137303255, articleId=1149738775342919919, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=融合异质层次因果图的尾矿堆积坝安全状态分析, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为探究尾矿堆积坝内外部因素对堆积坝体安全状态的影响,提出基于异质层次图的尾矿堆积坝安全状态分析方法。该方法通过构建异质层次因果图,将环境、渗流场和应力场等关键因素与堆积坝安全状态建立联系,并结合异质节点属性特征,形成环-渗-应安全状态分析指标体系;通过提出定量指标动态等级区间计算方法和安全状态等级计算模型,将坝体安全状态定性问题的模糊性转化为定量化表达,实现对尾矿堆积坝安全等级评价;以洛阳某尾矿坝为例验证模型的科学性。结果表明:该模型能合理定量分析因素与状态之间联系,并找出堆积坝负向演化的敏感性因素,给后续筑坝过程的安全管理提供决策依据。

, correspAuthors=韩思淼, authorNote=null, correspAuthorsNote=
** 韩思淼(1999—),女,安徽阜阳人,硕士研究生,研究方向为矿山安全智能分析。E-mail:
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阮顺领 (1981—),男,河南周口人,博士,教授,主要从事矿山系统优化与管理方面的研究。E-mail:

刘 迪 工程师;

江松 教授

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label=Fig.7, caption=Monitoring indicator values, figureFileSmall=paYj9JQt7n3tdIk2XTG2CQ==, figureFileBig=tiu0ocV8WcFLSEV840kCdw==, tableContent=null), ArticleFig(id=1168186576837288648, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=图7, caption=监测指标值, figureFileSmall=paYj9JQt7n3tdIk2XTG2CQ==, figureFileBig=tiu0ocV8WcFLSEV840kCdw==, tableContent=null), ArticleFig(id=1168186576900203209, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 1, caption=

Smaller-is-better indicator dynamic class intervals

, figureFileSmall=null, figureFileBig=null, tableContent=
等级 等级标准
H e > E n 3 H e E n 3
等级Ⅰ [ y m i n E x + 0.67 S] [ y m i n E x + 0.67 E n]
等级Ⅱ [ E x + 0.67 S E x + S] [ E x + 0.67 E n E x + E n]
等级Ⅲ [ E x + S E x + 2 S] [ E x + E n E x + 2 E n]
等级Ⅳ [ E x + 2 S 3 S],
y m a x < E x + 3 S
[ E x + 2 S y m a x], y m a x E x + 3 S
[ E x + 2 E n E x + 3 E n],
y m a x < E x + 3 E n
[ E x + 2 E n y m a x],
y m a x E x + 3 E n
), ArticleFig(id=1168186577026032330, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表1, caption=

越小越优型指标动态等级区间

, figureFileSmall=null, figureFileBig=null, tableContent=
等级 等级标准
H e > E n 3 H e E n 3
等级Ⅰ [ y m i n E x + 0.67 S] [ y m i n E x + 0.67 E n]
等级Ⅱ [ E x + 0.67 S E x + S] [ E x + 0.67 E n E x + E n]
等级Ⅲ [ E x + S E x + 2 S] [ E x + E n E x + 2 E n]
等级Ⅳ [ E x + 2 S 3 S],
y m a x < E x + 3 S
[ E x + 2 S y m a x], y m a x E x + 3 S
[ E x + 2 E n E x + 3 E n],
y m a x < E x + 3 E n
[ E x + 2 E n y m a x],
y m a x E x + 3 E n
), ArticleFig(id=1168186577109918411, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 2, caption=

Larger-is-better indicator dynamic class intervals

, figureFileSmall=null, figureFileBig=null, tableContent=
等级 等级标准
H e > E n 3 H e E n 3
等级Ⅰ [ E x - 0.67 S y m a x] [ E x - 0.67 E n y m a x]
等级Ⅱ [ E x - S E x - 0.67 S] [ E x - E n E x - 0.67 E n]
等级Ⅲ [ E x - 2 S E x - S] [ E x - 2 E n E x - E n]
等级Ⅳ [ E x - 3 S E x - 2 S],
y m i n E x - 3 S
[ y m i n E x - 2 S],
y m i n < E x + 3 S
[ E x - 3 E n E x - 2 E n],
y m i n E x - 3 E n
[ y m i n E x - 2 E n],
y m i n < E x - 3 E n
), ArticleFig(id=1168186577189610188, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表2, caption=

越大越优型指标动态等级区间

, figureFileSmall=null, figureFileBig=null, tableContent=
等级 等级标准
H e > E n 3 H e E n 3
等级Ⅰ [ E x - 0.67 S y m a x] [ E x - 0.67 E n y m a x]
等级Ⅱ [ E x - S E x - 0.67 S] [ E x - E n E x - 0.67 E n]
等级Ⅲ [ E x - 2 S E x - S] [ E x - 2 E n E x - E n]
等级Ⅳ [ E x - 3 S E x - 2 S],
y m i n E x - 3 S
[ y m i n E x - 2 S],
y m i n < E x + 3 S
[ E x - 3 E n E x - 2 E n],
y m i n E x - 3 E n
[ y m i n E x - 2 E n],
y m i n < E x - 3 E n
), ArticleFig(id=1168186577277690573, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 3, caption=

Classification results of indicators

, figureFileSmall=null, figureFileBig=null, tableContent=
参数指标 分级标准
I级 Ⅱ级 Ⅲ级 Ⅳ级
降雨量X11/mm [0,0.11) [0.11,0.214) [0.214,9.4) [9.4,80]
地震烈度 X 1 2/度 [0,3) [3,6) [6,9) [9,15]
地形地质 X 1 3 [0.8,1) [0.35,0.8) [0.05,0.35) [0,0.05]
排放工艺 X 1 4 [1.3,1.37) [1.37,1.38) [1.38,1.40) [1.40,1.43]
库水位X21/m [1 431.67,1 432.19) [1 432.19,1 432.23) [1 432.23,1 432.35) [1 432.35,1 432.48]
浸润线X22/m [19.32,37.65) [37.65,39.52) [39.52,45.19) [45.19,50.86]
干滩长度X23/m [310.58,546.58] [298.55,310.58) [262.09,298.55) [224.8,262.09)
渗流量X24/(L·s-1) [0,0.01) [0.01,1) [1,10) (10,20]
表面位移X31/mm [-0.28,0] [-0.34,-0.28) [-0.52,-0.34) [-13.29,-0.52)
[0,1.98) [1.98,2.79) [2.79,5.23) [5.23,40]
内部位移X32/mm [-0.77,0] [-1.10,-0.77) [-2.10,-1.10) [-20.30,-2.10)
[0,0.80) [0.80,1.14) [1.14,2.17) [2.17,20.30]
安全超高X33/m [4.19,7.21] [4.03,4.19) [3.54,4.03) [3.05,3.54)
尾矿性质X34/mm [0,0.1) [0.1,0.3) [0.3,0.6) [0.6,1.0]
), ArticleFig(id=1168186577348993742, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表3, caption=

指标分级结果

, figureFileSmall=null, figureFileBig=null, tableContent=
参数指标 分级标准
I级 Ⅱ级 Ⅲ级 Ⅳ级
降雨量X11/mm [0,0.11) [0.11,0.214) [0.214,9.4) [9.4,80]
地震烈度 X 1 2/度 [0,3) [3,6) [6,9) [9,15]
地形地质 X 1 3 [0.8,1) [0.35,0.8) [0.05,0.35) [0,0.05]
排放工艺 X 1 4 [1.3,1.37) [1.37,1.38) [1.38,1.40) [1.40,1.43]
库水位X21/m [1 431.67,1 432.19) [1 432.19,1 432.23) [1 432.23,1 432.35) [1 432.35,1 432.48]
浸润线X22/m [19.32,37.65) [37.65,39.52) [39.52,45.19) [45.19,50.86]
干滩长度X23/m [310.58,546.58] [298.55,310.58) [262.09,298.55) [224.8,262.09)
渗流量X24/(L·s-1) [0,0.01) [0.01,1) [1,10) (10,20]
表面位移X31/mm [-0.28,0] [-0.34,-0.28) [-0.52,-0.34) [-13.29,-0.52)
[0,1.98) [1.98,2.79) [2.79,5.23) [5.23,40]
内部位移X32/mm [-0.77,0] [-1.10,-0.77) [-2.10,-1.10) [-20.30,-2.10)
[0,0.80) [0.80,1.14) [1.14,2.17) [2.17,20.30]
安全超高X33/m [4.19,7.21] [4.03,4.19) [3.54,4.03) [3.05,3.54)
尾矿性质X34/mm [0,0.1) [0.1,0.3) [0.3,0.6) [0.6,1.0]
), ArticleFig(id=1168186577449657039, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 4, caption=

Results of status level assessment

, figureFileSmall=null, figureFileBig=null, tableContent=
评估等级
SHI(H) 2.063 9 1.573 2 1.780 0 1.713 3
s 0.289 5 0.220 6 0.249 6 0.240 3
置信区间 0.289 5 0.510 1
), ArticleFig(id=1168186577579680464, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表4, caption=

状态等级评估结果

, figureFileSmall=null, figureFileBig=null, tableContent=
评估等级
SHI(H) 2.063 9 1.573 2 1.780 0 1.713 3
s 0.289 5 0.220 6 0.249 6 0.240 3
置信区间 0.289 5 0.510 1
), ArticleFig(id=1168186577638400721, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 5, caption=

Results of status level assessment

, figureFileSmall=null, figureFileBig=null, tableContent=
参数指标 评估等级 参数指标 评估等级
X 11 X 23
X 12 X 24
X 13 X 31
X 14 X 32
X 21 X 33
X 22 X 34
), ArticleFig(id=1168186577751646930, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表5, caption=

状态等级评估结果

, figureFileSmall=null, figureFileBig=null, tableContent=
参数指标 评估等级 参数指标 评估等级
X 11 X 23
X 12 X 24
X 13 X 31
X 14 X 32
X 21 X 33
X 22 X 34
), ArticleFig(id=1168186577902641875, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 6, caption=

Minimum safety factors for slip resistance and stability

, figureFileSmall=null, figureFileBig=null, tableContent=
坝体级别 1 2 3
运行
工况
瑞典圆
弧法
简化毕
肖普法
瑞典圆
弧法
简化毕
肖普法
瑞典圆
弧法
简化毕
肖普法
正常运行 1.30 1.50 1.25 1.35 1.20 1.30
), ArticleFig(id=1168186578032665300, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表6, caption=

抗滑稳定最小安全系数

, figureFileSmall=null, figureFileBig=null, tableContent=
坝体级别 1 2 3
运行
工况
瑞典圆
弧法
简化毕
肖普法
瑞典圆
弧法
简化毕
肖普法
瑞典圆
弧法
简化毕
肖普法
正常运行 1.30 1.50 1.25 1.35 1.20 1.30
), ArticleFig(id=1168186578099774165, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=EN, label=Table 7, caption=

Calculated parameters for stability of each soil layer of the tailings dam

, figureFileSmall=null, figureFileBig=null, tableContent=
地层 指标
天然重度γ/
(kN·m-3)
固结快剪 渗透系数/
(cm·s-1)
黏聚力
C/kPa
内摩擦角
ϕ/(°)
人工填土-1 20.0 20 18
人工填土-2 22.0 0 40
尾细砂 22.6 0 85
尾粉砂 21.1 13.0 33.0 1.65-4
尾粉土 21.4 12.0 30.0 4.93×10-5
尾粉质黏土 21.7 14.0 26.0 1.34-5
尾黏土 17.3 18.0 19.0 6.01-6
粉质黏土 19.1 17.0 15.0 1.65×10-6
强风化、中风
化基岩层
23.0 18.0 19.0 9.32-6
), ArticleFig(id=1168186578221408982, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149738775342919919, language=CN, label=表7, caption=

库区各土层稳定计算参数

, figureFileSmall=null, figureFileBig=null, tableContent=
地层 指标
天然重度γ/
(kN·m-3)
固结快剪 渗透系数/
(cm·s-1)
黏聚力
C/kPa
内摩擦角
ϕ/(°)
人工填土-1 20.0 20 18
人工填土-2 22.0 0 40
尾细砂 22.6 0 85
尾粉砂 21.1 13.0 33.0 1.65-4
尾粉土 21.4 12.0 30.0 4.93×10-5
尾粉质黏土 21.7 14.0 26.0 1.34-5
尾黏土 17.3 18.0 19.0 6.01-6
粉质黏土 19.1 17.0 15.0 1.65×10-6
强风化、中风
化基岩层
23.0 18.0 19.0 9.32-6
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融合异质层次因果图的尾矿堆积坝安全状态分析
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阮顺领 1, 2, 3 , 韩思淼 1, 2, ** , 殷一涵 1 , 刘迪 1, 3 , 刘佳佳 1, 2 , 江松 1, 2, 3
中国安全科学学报 | 安全工程技术 2024,34(7): 53-62
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中国安全科学学报 | 安全工程技术 2024, 34(7): 53-62
融合异质层次因果图的尾矿堆积坝安全状态分析
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阮顺领1, 2, 3 , 韩思淼1, 2, ** , 殷一涵1, 刘迪1, 3, 刘佳佳1, 2, 江松1, 2, 3
作者信息
  • 1 西安建筑科技大学 资源工程学院,陕西 西安 710055
  • 2 西安建筑科技大学 矿山系统工程研究所,陕西 西安 710055
  • 3 西安市智慧工业感知计算与决策重点实验室,陕西 西安 710055
  • 阮顺领 (1981—),男,河南周口人,博士,教授,主要从事矿山系统优化与管理方面的研究。E-mail:

    刘 迪 工程师;

    江松 教授

通讯作者:

** 韩思淼(1999—),女,安徽阜阳人,硕士研究生,研究方向为矿山安全智能分析。E-mail:
Tailings accumulation dam safety state analysis by integrating heterogeneous hierarchical graph
Shunling RUAN1, 2, 3 , Simiao HAN1, 2, ** , Yihan YIN1, Di LIU1, 3, Jiajia LIU1, 2, Song JIANG1, 2, 3
Affiliations
  • 1 School of Resources Engineering,Xi'an University of Architecture and Technology,Xi'an Shaanxi 710055,China
  • 2 Institute of Mine Systems Engineering,Xi'an University of Architecture and Technology,Xi'an Shaanxi 710055,China
  • 3 Xi'an Key Laboratory of Perceptive Computing and Decision for Intelligent Industry,Xi'an Shaanxi 710055,China
出版时间: 2024-07-28 doi: 10.16265/j.cnki.issn1003-3033.2024.07.1892
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为探究尾矿堆积坝内外部因素对堆积坝体安全状态的影响,提出基于异质层次图的尾矿堆积坝安全状态分析方法。该方法通过构建异质层次因果图,将环境、渗流场和应力场等关键因素与堆积坝安全状态建立联系,并结合异质节点属性特征,形成环-渗-应安全状态分析指标体系;通过提出定量指标动态等级区间计算方法和安全状态等级计算模型,将坝体安全状态定性问题的模糊性转化为定量化表达,实现对尾矿堆积坝安全等级评价;以洛阳某尾矿坝为例验证模型的科学性。结果表明:该模型能合理定量分析因素与状态之间联系,并找出堆积坝负向演化的敏感性因素,给后续筑坝过程的安全管理提供决策依据。

异质层次因果图  /  尾矿堆积坝  /  安全状态  /  云模型  /  集对分析

In order to investigate the influence of internal and external factors on the safety state of the tailings dam,a method for analysing the safety state of the tailings dam based on heterogeneous hierarchical diagrams was proposed. Firstly,a hierarchical causal graph was constructed based on a priori knowledge to link key factors such as environment,seepage field and stress field with the safety status of tailing dams,and an evaluation index system was established by combining the attribute characteristics of heterogeneous nodes. Secondly,the cloud model and set-pair analysis theory were used to quantitatively calculate the potential logical relationship between the heterogeneous causal graph and the safety stability of the tailings dam. A dynamic interval calculation method for quantitative indicators and a safety status level calculation model were proposed to convert the fuzziness and uncertainty of complex and diverse evaluation indicators into quantitative expressions. Finally,a tailings dam in Luoyang was used as an example to verify the scientificity of the model.The results show that the model can quantitatively analyse the link between factors and states and identify the causes of negative changes in stacked dams. The conclusions of the model analysis can be used for the safety management of the dam-building process.

heterogeneous hierarchical causal graph  /  tailings accumulation dam  /  safety situation  /  cloud model  /  set pair analysis
阮顺领, 韩思淼, 殷一涵, 刘迪, 刘佳佳, 江松. 融合异质层次因果图的尾矿堆积坝安全状态分析. 中国安全科学学报, 2024 , 34 (7) : 53 -62 . DOI: 10.16265/j.cnki.issn1003-3033.2024.07.1892
Shunling RUAN, Simiao HAN, Yihan YIN, Di LIU, Jiajia LIU, Song JIANG. Tailings accumulation dam safety state analysis by integrating heterogeneous hierarchical graph[J]. China Safety Science Journal, 2024 , 34 (7) : 53 -62 . DOI: 10.16265/j.cnki.issn1003-3033.2024.07.1892
废弃尾矿处理形成的构筑物称为尾矿储存设施(Tailings Storage Facilities,TSF),尾矿堆积坝作为TSF最常见的存在形式[1]。尾矿坝的安全状态受各种不确定性因素共同作用的影响,据统计,全球超过10%溃坝事件是由于运行管理不善造成的[2]。尾矿坝溃坝、滑坡等地质灾害具有易发性、隐蔽性、危害性等特点。根据多项事故调查表明:灾难性的尾矿储存设施故障通常是人为造成的,而全面的监测与监管能减少事故灾害的发生[3]。因此,高效利用安全监测数据,探究外界因素与尾矿堆积坝的安全状态之间的因果关联,对实现尾矿坝安全状态实时分析和风险评价具有重要的科学理论意义和工程现实意义。
随着计算机通信、传感器技术的突飞猛进,监测手段和信息采集、传输方式发生巨变,各种类型的自动监测设备应用于矿山安全生产中,提高了监测效率和自动化程度[4-5]。如BUSELLI等[6]成功监测了矿区的渗流,这是对尾矿库监测的初步探索;蒋卫东等[7]提出浸润线变化的混沌系统的概念,并以最大Lyapunov指数作为浸润线状态评价指标,为监测数据理论分析提供了新思路。传感器布置于堆积坝体的不同位置,监测相同或不同的安全稳定性的关键参数。故此,基于降雨、浸润线、变形等监测数据的安全评价是解决安全预警问题的常用手段[8]。如杨春和等[9]建立了复杂条件下高尾矿坝性能劣化理论,系统描述了尾矿坝从成坝到运行的性能演化全过程;颜学军[10]基于尾矿沉积固结特性,提出尾矿排放浓度、流速、流量、排放点等因素对坝体沉积特征及坝体结构组成的影响机制。多源监测数据从不同的角度提供研究对象的信息,丰富网络信息,为尾矿坝的安全评估提供数据支撑。目前主要采用安全系数法、综合评价法、人工智能法进行尾矿坝安全稳定性分析。安全系数法适用于尾矿坝的特定时间和工况[11],对变异系数进行假设或简单计算。综合评价法采用模糊数学、可拓理论、集对分析理论等处理定性概念与定量描述的不确定性。李辉等[12]将未知数学理论引入尾矿坝稳定性综合评价中,建立因素空间-未确知测度模型,并通过因素合成实现因素空间降维;潘科等[13]引入三角模糊理论解决了尾矿坝评价中指标权重的模糊性,边界不清等问题;戴剑勇等[14]提出基于网络云模型的尾矿库溃坝关键节点分析方法,为定量分析尾矿库溃坝中的关键隐患节点提供了一种新途径;柯丽华等[15]针对尾矿库日常安全管控的需求,采用集对分析方法和可拓理论,提出基于集对可拓侧距关联算法的尾矿库安全态势及其敏感因素分析模型。人工智能法能挖掘监测数据与尾矿坝稳定性之间的非线性的复杂关系,并以逻辑推理的方式来评估尾矿坝的安全稳定性,但对参数的选择以及数据集的规模要求较高。DONG Kai等[16]利用径向基函数神经网络(Radial Basis Function Neural Network,RBF)构建异常数据的环境量响应模型,建立了尾矿坝安全评价的耦合关系;刘迪等[17]结合贝叶斯决策理论确定了干滩长度的监测预警阈值,为尾矿坝稳定性状况的判断提供了新思路。以上方法少有结合坝体性能演化与因果分析的综合指标进行分析。但在实际工程中,堆积坝的安全状态具有模糊性和不确定性,且各因素与安全状态之间的影响效果难以量化,增加了安全状态分析的难度。
鉴于此,笔者将以多源监测数据为研究对象,从图表的角度分析堆积坝安全因素之间的潜在关联,构建环-渗-应异质信息指标体系。并采用集对云模型量化拓扑结构和关联实体属性对堆积坝安全状态的影响,解决堆积坝体安全状态的模糊性与不确定性,以期为筑坝过程中的安全管理提供科学的决策依据和理论支撑。
从尾矿堆积的安全角度分析,提出的安全状态分级模型,如图1所示。
异质层次因果图是一种用于描述系统中不同层次之间因果关系的图形表示方法,旨在更全面地揭示系统内部的复杂因果关系。构建异质层次拓扑结构问题的关键是引入哪些实体属性信息,在文中,根据尾矿坝演化关系网络包含的信息类型,构建包含3种类型节点的层次因果图,即环境变量、渗流监测、应力应变,用以反映堆积坝的安全状态。
1) 层次节点。尾矿坝在全生命周期内受环境状况扰动而时刻变化,因此,在运行过程中,每一时刻的尾矿坝的状态对应着几组可能的3要素(环境、渗流、应力),反映环境变化与尾矿坝内部渗流场和应力场之间的关系。
s = ( { c 1 c 2 c i } { p 1 p 2 p j } { f 1 f 2 f k } )
式中:s为运行中尾矿堆积坝的当前状态;ci维环境变量;pj维渗流变量;fk维应力变量。尾矿堆积坝体的现行状态随环境、渗流场、应力场的变化而共同变化。当环境状况c给定时,模型的任务是计算相应的渗流变化p和应力f变化,进而反映尾矿堆积坝所处的安全状态。
2) 异质层次因果图。用有向图 G s = ( V s E s )表示尾矿堆积运行过程中发生的环-渗-应因果关系, V s = { c p f }节点集合, E s : { c p p f c f }边的集合,其中,V由节点cpf组成。环境和渗流间的边 c p = ( c i p j )。渗流和应力间的边 p f = ( p j f k )。环境和渗流之间的边 c f = ( c i f k )。尾矿堆积坝异质层次因果如图2所示。尾矿堆积坝异质层次图是由3个异质图(环-渗图,渗-应图,环-应图)组成。这种子集关系建立了层次结构,使得整个图呈现出清晰的层次性,有助于从整体到局部的分析。
尾矿堆积坝属于水利沉积物[18],影响其稳定性的因素绝大部分都是动态不确定性的,如尾矿含水量的空间变迁性、尾矿堆积坝工程的时变性和安全破坏的渐进性等。图结构的抽象使得网络基础结构更加清晰,但现有研究大多基于溃坝关联关系构建同质网络或不区分关联关系的差异性构建同质网络[19-21]。异质层次因果图异质性分析如图3所示,异质层次因果图动态性分析如图4所示。
从系统工程的角度看,堆积坝的安全性和稳定性受到坝体渗流场、应力场和外界环境变量的共同影响[22-23]。在尾矿堆积坝安全状态的分析中,异质层次因果图通过考虑动态不确定性的因素,帮助理解尾矿坝系统中各要素之间的因果关系,包括不同层次的元素如何相互影响,以及它们的异质性特征如何影响整个系统的行为,有助于深入分析堆积坝与实体之间的复杂交互性作用及其演化过程,以确保尾矿坝在长期运行中的可持续安全性。
在评价尾矿库运行及安全状态时,重点在于尾矿库自然状况、尾矿堆坝方式、坝体形变及渗流等,并根据勘察资料或经验数据定量分析尾矿坝稳定性。参考《尾矿库安全规程》[24]及其他相关研究成果[25]划定尾矿库体系,选取环境变量、渗流监测、应力应变3大类指标构建指标体系,并将12个节点属性作为评估因子,将尾矿堆积坝的安全状态划分为4个等级,建立定性与定量相结合的环-渗-应异质信息指标体系,如图5所示。
为适应复杂异构的指标体系和多元评估实体,解决评估区间的主观性,利用云模型表达尾矿坝安全态势的定性概念与其安全状态级别的定量数值关系,定性概念与定量数值之间的纽带为正态云模型和联系数的耦合模型,基于环境、渗流、应力应变等不同类别的监测项目,分析堆积坝各关键场的变化趋势,进而评估堆积坝体的运行安全状况。
针对评价对象的特殊性、模糊性以及不确定性的特点,将定性问题“评价指标与评价标准的联系”定量表达为评价标准与评价结果之间的联系隶属度函数,为各监测指标评价等级区间划分提供基础。根据因素指标与稳定性之间的特性,指标等级区间分为越小越优型和越大越优型。地震烈度以及地形地质等定性评价指标的等级评价区间参考规范进行划定。对于持续监测的数据指标,利用逆向云发生器将评价标准的不确定性量化为云模型参数。结合考虑不同区域内云滴对定性概念的贡献度,实现动态等级标准的建立,不同区域内云滴对定性概念的贡献如图6所示。
具体的计算流程如下:
输入:样本 ( x 1 x 2 x n )
输出:数字特征ExEnHe
1) 计算 ( x 1 x 2 x n )中的样本期望
x - = 1 n i = 1 n x i
E x = x -
2) 计算 ( x 1 x 2 x n )中的样本熵值
E n = π 2 · i = 1 n | x i - E x |
3) 计算 ( x 1 x 2 x n )中的样本超熵
S 2 = 1 n - 1 i = 1 n x i - x - 2
H e = | S 2 - E 2 n |
H e > E n 3,则产生雾化现象,此时根据均值、标准差划分等级区间。若 H e E n 3,则云滴符合正态分布,根据均值和熵值划分。越小越优型和越大越优型指标划分方法分别见表1表2
尾矿堆积坝的安全状态受多元的因素影响具有异质性、动态性和关联性的特点,因此,环-渗-应异质信息指标与安全状态等级之间存在着一定的关联性,结合集对分析理论,计算评价指标与评价等级之间的综合联系度,感知尾矿堆积坝的安全状态,再根据经验公式复核评价结果。具体的计算流程如下:
1) 指标联系度的计算。采用距离贴近度的方法计算各指标联系度系数,确定联系度表达式。具体公式如下:
μ 1 = 1 q i [ X 0 X 1 ) X 1 - X 0 q i - X 0 + q i - X 1 q i - X 0 i q i [ X 1 X 2 ) X 1 - X 0 q i - X 0 + X 2 - X 1 q i - X 0 i + q i - X 2 q i - X 0 j q i [ X 2 X 4 ]
μ 2 = X 2 - X 1 X 2 - q i + X 1 - q i X 2 - q i i q i [ X 0 X 1 ) 1 q i [ X 1 X 2 ) X 2 - X 1 q i - X 1 + q i - X 2 q i - X 1 i q i [ X 2 X 3 ) X 2 - X 1 q i - X 1 + X 3 - X 2 q i - X 1 i + q i - X 3 q i - X 1 j q i [ X 3 X 4 ]
μ 3 = X 3 - X 2 X 3 - q i + X 2 - X 1 X 3 - q i i + X 1 - q i X 3 - q i j q i [ X 0 X 1 ) X 3 - X 2 X 3 - q i + X 2 - q i X 3 - q i i q i [ X 1 X 2 ) 1 q i [ X 2 X 3 ) X 3 - X 2 q i - X 2 + q i - X 3 q i - X 2 i q i [ X 3 X 4 ]
μ 4 = X 4 - X 3 X 4 - q i + X 3 - X 2 X 4 - q i i + X 2 - q i X 4 - q i j q i [ X 0 X 2 ) X 4 - X 3 X 4 - q i + X 3 - q i X 4 - q i i q i [ X 2 X 3 ) 1 q i [ X 3 X 4 ]
式中:qi为第 i项指标的指标值;Xj为第 i项指标的第j个等级的标准的临界值。
2) 状态等级的确定。综合考虑定量与定性因素,根据上一步单指标联系度构成的分析矩阵R与指标权重向量w,计算尾矿堆积坝安全状态的综合联系度矩阵H。计算集对势SHI,并对结果归一化处理。依据置信度准则,取置信度 λ为0.5,当满足s1+s2+…+sj λ时,对应的等级j即为尾矿堆积坝所属等级,如下式:
H = w · R
S H I ( H ) = e a 1 e c 1 e a 2 e c 2 e a k e c k
s j = S H I ( H j ) i = 1 k S H I ( H i )
在尾矿坝安全评价研究中,常利用土体力学参数来计算安全系数,分析边坡稳定。因此,为验证文中所提方法的有效性,采用瑞典圆弧法计算坝体安全系数,复核评价结果。计算式为:
K = { d b s e c Ø + ( W i c o s Ø - u b s e c Ø ) t g Ø } W s i n Ø
式中:K为安全系数;b为滑块土条宽度,m;Ø为土条底面中心点切线与水平线的夹角,(°);u为土条底面的孔隙压力,kPa;Wi为计入渗透压力后的土条重量,计算时浸润线以上用湿重度,下游水位以下用浮重度;浸润线以下至下游水位间,当计算抗滑力时用浮重度,计算滑动力时用湿重度,kN/m3;d为土在地震作用下的总应力抗剪切指标,kPa。
针对安全状态分析方法,选用洛阳某尾矿库进行应用分析。该尾矿库为二等库,抗震设防烈度为6级,尾矿平均粒径0.119mm,现有排水系统由排水隧洞和排水井组成的排渗席垫排渗总流量为1 000m3/d,属于上游式湿排尾矿库。该尾矿库使用在线监测系统进行安全监测,监测项目包含降雨量、滩面长度、干滩坡比、库水位、浸润线、表面位移、内部位移等。
部分监测项目的监测数据如图7所示。基于以上尾矿库的基础数据和采集2023年1月—4月的监测数据,采用动态等级区间计算方法分析处理数据,建立堆积坝体多元监测数据的动态等级区间。计算单指标因素的 E x E n H e,最终得到河南洛阳某尾矿坝的动态等级指标区间见表3
根据层次分析法,得出堆积坝状态指标权重w为(0.071 1,0.059 3,0.017 7,0.059 3,0.106 5,0.131 2,0.131 2,0.047 4,0.140 8,0.140 8,0.035 4,0.059 3)。
根据模型计算堆积坝12个评价指标与4个评价等级标准之间的联系度,计算结果如下:
降雨量:
μ 1 = 1       μ 2 = 0.486   0 + 0.514   0 i       μ 3 = 0.977   2 + 0.011   0 i + 0.011   7 j       μ 4 = 0.882   5 + 0.114   8 i + 0.002   7 j
地震烈度:
μ 1 = 0.500   0 + 0.500   0 i       μ 2 = 1       μ 3 = 1       μ 4 = 0.666   7 + 0.333   3 i
地形地质:
μ 1 = 0.800   0 + 0.200   0 i       μ 2 = 1       μ 3 = 0.428   6 + 0.571   4 i       μ 4 = 0.066   7 + 0.400   0 i + 0.533   3 j
排放工艺:
μ 1 = 1       μ 2 = 0.500   0 + 0.500   0 i       μ 3 = 0.600   0 + 0.200   0 i + 0.200   0 j       μ 4 = 0.375   0 + 0.375   0 i + 0.250   0 j
库水位:
μ 1 = 0.753   6 + 0.188   4 i + 0.188   4 j       μ 2 = 0.235   3 + 0.705   9 i + 0.058   8 j       μ 3 = 0.923   1 + 0.076   9 i       μ 4 = 1
浸润线:
μ 1 = 1       μ 2 = 0.474   6 + 0.525   4 i       μ 3 = 0.590   0 + 0.194   6 i + 0.215   4 j       μ 4 = 0.371   1 + 0.371   1 i + 0.257   9 j
干滩长度:
μ 1 = 1       μ 2 = 0.568   3 + 0.431   7 i       μ 3 = 0.632   7 + 0.208   7 i + 0.158   6 j       μ 4 = 0.706   4 + 0.185   8 i + 0.107   9 j
渗流量:
μ 1 = 0.000   9 + 0.085   6 i + 0.913   6 j       μ 2 = 0.085   6 + 0.778   5 i + 0.135   8 j       μ 3 = 0.851   5 + 0.148   5 i       μ 4 = 1
表面位移:
μ 1 = 1       μ 2 = 0.358   4 + 0.641   6 i       μ 3 = 0.519   1 + 0.172   3 i + 0.308   5 j       μ 4 = 0.880   9 + 0.061   8 i + 0.057   3 j
内部位移:
μ 1 = 0.544   2 + 0.231   3 i + 0.224   5 j       μ 2 = 0.507   5 + 0.492   5 i       μ 3 = 1       μ 4 = 0.962   8 + 0.037   2 i
安全超高:
μ 1 = 1       μ 2 = 0.290   9 + 0.709   1 i       μ 3 = 0.471   2 + 0.153   8 i + 0.375 j       μ 4 = 0.320   2 + 0.320   3 i + 0.359   5 j
尾矿性质:
μ 1 = 0.840   3 + 0.159   7 i       μ 2 = 1       μ 3 = 0.623   7 + 0.376   3 i       μ 4 = 0.454   0 + 0.340   5 i + 0.205   4 j
结合权重计算尾矿坝状态综合联系度向量:
H = w · R = 0.819   6 + 0.099   3 i + 0.095   0 j   0.465   8 + 0.521   5 i + 0.01   27 j   0.719   9 + 0.136   9 i + 0.143   3 j   0.674   2 + 0.194   3 i + 0.135   8 j
计算尾矿堆积坝体在4个等级的广义集对势值,并进行归一化处理,安全状态计算结果见表4
状态等级评估结果见表5。根据置信度准则判断,得出当前尾矿堆积坝体安全状态为等级Ⅱ:良好。同时,根据集对分析相关理论可以得出,该尾矿堆积坝在等级Ⅱ为微同势,在等级Ⅲ表现为强同势,因此,虽然目前堆积坝体较为安全,但有向不稳定发展的趋势,需要进一步分析影响堆积坝整体安全的敏感性因素。
表5可知:降雨量、库水位、渗流量和内部位移的安全状态为等级Ⅲ,可能是堆积坝负向状态发展的原因,因此,需要在后续的管理中着重监管库内水位和坝体位移。
尾矿库所在地区抗震设防烈度为6度,不考虑地震,采用极限平衡法分析坝体稳定性,坝坡抗滑稳定要求的最小安全系数见表6,稳定性计算参数见表7
通过稳定性验算堆积坝体,其最小稳定系数K为1.331,按《尾矿设施设计规范》(GB50863—2013)有关评价标准(稳定系数K=1.25):堆积坝体处于稳定状态,与上述状态感知模型得出评价结果一致,表明该模型的合理性。
1) 引入异质层次因果图的概念,将堆积坝安全状态与环境、渗流、应力各节点特征相关联。并借助多源监测数据与集对云概念,有效分析因素对安全状态与趋势的影响,避免了评估模型的主观性和模糊性。
2) 基于异质层次图构建尾矿堆积坝安全状态分级模型,应用于洛阳某尾矿坝,结果表明:该尾矿库的安全状态为良好,进一步分析得出库内水位和坝体位移是影响其安全状态发展趋势的敏感性因素,为决策者提供明确的管理建议。
3) 在层次节点的构建与选取时,受到现有理论、监测系统的局限,选取的环境、渗流、应力指标不全面。因此,应结合物理力学性质,细化因果图层次结构,进一步探讨尾矿堆筑过程的稳定性与影响因素之间的演化关联。
  • 国家自然科学基金资助(52374160)
  • 陕西省自然科学基础研究计划项目(2022JM-201)
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2024年第34卷第7期
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doi: 10.16265/j.cnki.issn1003-3033.2024.07.1892
  • 接收时间:2024-01-11
  • 首发时间:2025-07-09
  • 出版时间:2024-07-28
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  • 收稿日期:2024-01-11
  • 修回日期:2024-04-13
基金
国家自然科学基金资助(52374160)
陕西省自然科学基础研究计划项目(2022JM-201)
作者信息
    1 西安建筑科技大学 资源工程学院,陕西 西安 710055
    2 西安建筑科技大学 矿山系统工程研究所,陕西 西安 710055
    3 西安市智慧工业感知计算与决策重点实验室,陕西 西安 710055

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** 韩思淼(1999—),女,安徽阜阳人,硕士研究生,研究方向为矿山安全智能分析。E-mail:
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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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