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黄金科学技术 ›› 2020, Vol. 28 ›› Issue (3): 372-379.doi: 10.11872/j.issn.1005-2518.2020.03.194

• 采选技术与矿山管理 • 上一篇    下一篇

基于综合决策云模型的围岩稳定性分级方法研究

周科平(),侯霄峰(),林允   

  1. 中南大学资源与安全工程学院,湖南 长沙 410083
  • 收稿日期:2019-12-05 修回日期:2020-03-12 出版日期:2020-06-30 发布日期:2020-07-01
  • 通讯作者: 侯霄峰 E-mail:kpzhou@vip.163.com;houxiaofeng1994@sina.com
  • 作者简介:周科平(1964-),男,湖南衡阳人,教授,博士生导师,从事矿业工程方面的研究工作。kpzhou@vip.163.com
  • 基金资助:
    国家自然科学基金项目“高寒冻融区露天矿岩质边坡裂隙网络扩展性多尺度时变演化机制”(51774323)

Research on Classification Method of Surrounding Rock Stability Based on Comprehensive Decision Cloud Model

Keping ZHOU(),Xiaofeng HOU(),Yun LIN   

  1. School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China
  • Received:2019-12-05 Revised:2020-03-12 Online:2020-06-30 Published:2020-07-01
  • Contact: Xiaofeng HOU E-mail:kpzhou@vip.163.com;houxiaofeng1994@sina.com

摘要:

地下工程围岩稳定性分析关系到地下工程的安全,围岩的稳定与否直接决定着地下工程的成败,因此开展地下工程围岩稳定性评价具有十分重要的意义。基于云理论,选取岩石单轴饱和抗压强度、完整性系数、岩石基本质量指标、地下水影响修正系数和软弱结构面产状影响系数作为围岩稳定性分级指标,综合运用DEMATEL决策模型和熵权法获取上述指标体系的组合权重,并选取公路隧道工程20组实测数据作为学习样本,建立围岩稳定性分级的综合决策云模型,将其应用于小红石砬子玉石矿5组工程围岩的稳定性分级实例中。结果表明:综合决策云模型判别结果与实际情况相吻合,判别准确率可达80%,且优于K-最邻近算法和随机森林算法的判别结果,说明所建立的综合决策云模型在工程实际中具有一定的应用价值,为围岩稳定性分级提供了新思路。

关键词: 围岩, 稳定性分级, 云模型, DEMATEL决策模型, 熵权法

Abstract:

The stability analysis of surrounding rock of underground engineering is related to the safety of underground engineering.The stability of surrounding rock directly determines the success or failure of the underground engineering.Therefore,it is of great significance to carry out the stability evaluation of surrounding rock of underground engineering.Based on cloud theory,the rock uniaxial saturation compressive strength,integrity coefficient,basic rock quality index,groundwater impact correction coefficient,and weak structure surface condition impact coefficient were selected as the surrounding rock stability classification indicators.The combination weight of the above index system was obtained by using DEMATEL decision-making model and entropy weight method,and then 20 sets of measured data of highway tunnel engineering were selected as learning samples to establish a comprehensive decision cloud model for surrounding rock stability classification.It is applied to an example of surrounding rock stability classification for 5 groups of Xiaohongshilazi jade mine.The results show that the discrimination result of the comprehensive decision cloud model is consistent with the actual situation,and the discrimination accuracy can reach 80%,which is better than the discrimination results of the K-nearest neighbor algorithm and the random forest algorithm,indicating that the comprehensive decision cloud model established in this paper has certain application value in engineering practice and can provide a new idea for stability classification of surrounding rocks.

Key words: surrounding rocks, stability classification, cloud model, DEMATEL decision model, entropy weight method

中图分类号: 

  • TD26

表1

围岩稳定性指标分级标准"

类别Rc/MPaKvRQD/%K1K2
>2001.00~0.7590~1000~0.20~0.1
100~2000.50~0.7575~900.2~0.40.1~0.2
50~1000.30~0.5050~750.4~0.60.2~0.4
25~500.15~0.3025~500.6~0.80.4~0.5
0~250~0.150~250.8~1.0>0.5

表2

标准化云模型数字特征"

类别ExEnHe
0.10.08490.001
0.30.08490.001
0.50.08490.001
0.70.08490.001
0.90.08490.001

图1

标准化云模型"

表3

隧道围岩分析数据"

样本Rc/MPaKvRQD/%K1K2实际级别
138.10.1618.700.3
237.10.1827.40.20.1
338.00.4590.00.40.1
438.00.3591.00.20.2
59.20.3075.00.40.2
617.40.3438.400.2
727.50.3739.700.2
856.80.5058.900
972.30.5362.800
1067.50.4558.900.2
1182.30.6679.800
1256.10.2941.500.2
1315.80.2739.300.1
1449.20.1929.800.6
1538.00.8093.00.30.2
1621.40.1725.90.30.1
1738.00.6092.00.20.2
1865.90.5869.300.2
1954.30.3033.60.10
2047.10.2527.50.20.3

表4

各评价指标组合权重"

指标Rc/MPaKvRQD/%K1K2
hi0.20660.22900.22550.17690.1620
wj0.08580.06660.15720.49380.1966
λi0.09450.08120.18890.46560.1698

表5

围岩稳定性分级结果"

样本综合确定度本文结果现场级别
U()U()U()U()U()
10.22900.01000.21310.10410.2931
20.12330.04670.18820.14360.3777
30.26930.04520.28700.14330.0598
40.13370.13090.33540.24410.0181
50.05030.20550.02380.15070.2372
60.23460.12050.03580.44270.2371
70.23320.12050.06310.58330.0676
80.31420.22420.44670.01180
90.29790.20900.36780.00280
100.28020.25380.41090.05240.0001
110.31410.42370.001900
120.23480.26160.08280.33250.1251
130.35100.03720.00880.28740.3697
140.22950.03650.15340.05080.4360
150.13730.12200.20350.19630.0262
160.12370.03800.00230.16800.5104
170.11870.16680.24160.30350.0008
180.27670.65320.08740.00020
190.18200.21010.07200.25500.1920
200.00010.03620.41810.08910.4258

表6

小红石砬子玉石矿工程实测数据和围岩分级结果"

序号Rc/MPaKvRQD/%K1K2综合确定度

本文

结果

KNNRF

现场

级别

U()U()U()U()U()
137.100.3790.00.10.20.13080.39370.17780.07500.0795
256.100.4560.000.10.30210.04530.37130.01770
323.280.1925.90.300.08000.000600.00300.4129
454.300.3436.80.10.10.18380.25800.33780.08210.1584
527.500.3539.30.10.20.00630.30080.11750.15450.3730
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