基于ANP的高海拔矿山掘进工作面通风方式优选

doi:10.11872/j.issn.1005-2518.2020.02.173

Abstract

Abstract:

Ventilation of tunneling face is an important part of mine ventilation system，which is of great signi-ficance for guaranteeing the health and life safety of workers.However，the special plateau environment with low pressure and low oxygen has put forward higher requirements for ventilation effect.According to the special environmental requirements of high altitude metal mine and based on analytic network process，11 evaluation indexes were established from three aspects of safety benefit，economic benefit and technical benefit.There is a complex interaction between the evaluation indexes of the ventilation effect of the heading face.The correlation of the evaluation indexes was obtained through group discussion among 12 researchers in the field of mine ventilation.Thus the network structure of ventilation effect evaluation index of heading face was established and the final evaluation system was formed.ANP method involves many elements，the calculation process is complex and the calculation is large.According to the analysis of the ventilation effect evaluation index of the tunneling face of the high-altitude mine and the result of correlation relationship construction，the ANP model diagram of ventilation effect evaluation of the tunneling face was established in the super decision software.The comprehensive weight of three ventilation modes and the global weight of each evaluation index were calculated to select the best ventilation method.This evaluation system was applied to a metal mine at an altitude of 3 400 m in Yunnan.Ten people，including experts in mine ventilation engineering and on-the-job mine ventilation technicians，were invited to fill in the pairwise comparison judgment matrix questionnaire.By comparing the importance of the two evaluation indexes，the judgment matrix was established，and the super decision software was used for relevant calculation.The results show that the comprehensive weight of far-pressing-near-suction ventilation mode ventilation mode is 46.16%，and its ventilation effect is the best.The global weight of “oxygen supply effect” is 20.08%，which is the most important evaluation index.The oxygen supply effect should be taken into account when choosing the ventilation mode of mining face at high altitude.It is proved by practice that the conclusions obtained by the evaluation system are in line with the actual safety of mines，and can point out the main factors to evaluate the ventilation effect of mines.

Key words: high altitude metal mines, drifting ventilation, ventilation scheme, analytic network process（ANP）, evaluation index, super decision software

CLC Number:

TD724

Rongrong LI,Zijun LI,Yilong HUANG,Shuqi ZHAO. Ventilation Mode Optimization of Mining Face at High Altitude Based on ANP[J].Gold Science and Technology, 2020, 28(2): 301-308.

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References 22

1	陆刚，韩可琦，肖桂彬.矿井通风系统可靠性的模糊综合评价[J].采矿与安全工程学报，2008，25（2）：244-247.
	Lu Gang，Han Keqi，Xiao Guibin.Fuzzy integrated evaluation for reliability of mine ventilating system[J].Journal of Mining and Safety Engineering，2008，25（2）：244-247.
2	王小军，司俊鸿，徐文全，等.基于可变模糊理论的矿井通风网络压能分布合理性研究[J].中国安全生产科学技术，2014，10（增1）：265-269.
	Wang Xiaojun，Si Junhong，Xu Wenquan，et al.Study on rationality of pressure distribution in mine ventilation network based on variable fuzzy theory[J].Journal of Safety Science and Technology，2014，10（Supp.1）：265-269.
3	尹土兵，王品，张鸣鲁.基于AHP及模糊综合评判的地下金属矿山安全分析与评价[J].黄金科学技术，2015，23（3）：60-66.
	Yin Tubing，Wang Pin，Zhang Minglu.Analysis and evaluation of safety in underground metal mine based on AHP and fuzzy evaluation method[J].Gold Science and Technology，2015，23（3）：60-66.
4	丁厚成，黄新杰.基于AHP-FCE的煤矿通风系统可靠性评价研究[J].自然灾害学报，2013，22（3）：153-159.
	Ding Houcheng，Huang Xinjie.AHP-FCE based reliability assessment of coal mine ventilation system[J].Journal of Natural Disasters，2013，22（3）：153-159.
5	王宏图，黄振华，范晓刚，等.粗糙集—神经网络理论在矿井通风系统评价中的应用[J].重庆大学学报，2011，34（9）：90-94.
	Wang Hongtu，Huang Zhenhua，Fan Xiaogang，et al.The application of rough sets-neural network theory to mine ventilation system evaluation[J].Journal of Chongqing University，2011，34（9）：90-94.
6	卢国斌，陈鹏，张俊武.BP神经网络的通风系统可靠性评价[J].辽宁工程技术大学学报（自然科学版），2014，33（1）：23-27.
	Lu Guobin，Chen Peng，Zhang Junwu.Ventilation system reliability evaluation based on BP neural network[J].Journal of Liaoning Technical University（Natural Science），2014，33（1）：23-27.
7	史秀志，周健.用Fisher判别法评价矿井通风系统安全可靠性[J].采矿与安全工程学报，2010，27（4）：562-567.
	Shi Xiuzhi，Zhou Jian.Reliability assessment for mine ventilation system safety using fisher discriminant analysis[J].Journal of Mining and Safety Engineering，2010，27（4）：562-567.
8	杨超，史秀志.基于Fisher判别法模型的矿山安全标准化等级评价[J].黄金科学技术，2018，26（2）：187-194.
	Yang Chao，Shi Xiuzhi.Mine safety standardization grade evaluation based on fisher discriminant mode[J].Gold Science and Technology，2018，26（2）：187-194.
9	陈明生，陈伯辉，沈斐敏.矿井通风优化评价指标体系权重确定[J].中国安全生产科学技术，2011，7（3）：22-25.
	Chen Mingsheng，Chen Bohui，Shen Peimin.Weight determination of evaluation index system in mine ventilation optimization[J].Journal of Safety Science and Technology，2011，7（3）：22-25.
10	韩艳杰，张志军，李亚俊.基于新型综合集成法的矿井通风系统安全评价[J].中国安全生产科学技术，2014，10（2）：75-80.
	Han Yanjie，Zhang Zhijun，Li Yajun.Evaluation of mine ventilation system safety based on new comprehensive integrated method[J].Journal of Safety Science and Technology，2014，10（2）：75-80.
11	陈建宏，覃曹原，刘栋.基于AHP和熵权VIKOR法的矿井通风系统优选[J].世界科技研究与发展，2016，38（5）：955-959.
	Chen Jianhong，Qin Caoyuan，Liu Dong.Optimization of mine ventilation system based on AHP and entropy weight VIKOR method[J].World Sci-Tech Research and Development，2016，38（5）：955-959.
12	张庆华.我国煤矿通风技术与装备发展现状及展望[J].煤炭科学技术，2016，44（6）：146-151.
	Zhang Qinghua.Development and prospect of mine ventilation technology and equipment[J].Coal Science and Technology，2016，44（6）：146-151.
13	龚剑，胡乃联，崔翔，等.高海拔矿山掘进通风方式优选[J].科技导报，2015，33（4）：56-60.
	Gong Jian，Hu Nailian，Cui Xiang，et al.Optimization of drifting ventilation method for high-altitude mine [J].Science and Technology Review，2015，33（4）：56-60.
14	袁剑波，崔钢，符秋生，等.基于网络分析法的公路桥梁施工安全风险评价研究[J].科技进步与对策，2014，31（11）：96-100.
	Yuan Jianbo，Cui Gang，Fu Qiusheng，et al.Study on safety risk evaluation of highway and bridge construction based on network analysis [J].Science and Technology Progress and Policy，2014，31（11）：96-100.
15	Tomás G N，Mónica G M，Silvia A D，et al.An environmental pressure index proposal for urban development planning based on the analytic network process[J].Environmental Impact Assessment Review，2008，29（5）：319-329.
16	Soota T.Integrated approach for sustainable product development using QFD and ANP[J].International Journal of Industrial and Systems Engineering，2017，25 （1）：59-75.
17	陈培友，侯甜甜.基于ANP—灰色模糊的社交网络舆情风险预警研究——以“重庆公交坠江事件”为例[J].情报科学，2019，37（5）：115-120.
	Chen Peiyou，Hou Tiantian.Research on the early warning of social network public opinion risk based on ANP-Gray fuzzy：Taking the“Chongqing bus falling river event”as an example[J].Information Science，2019，37（5）：115-120.
18	Wang X J，He L L，Zhu K Y，et al.An integrated model to evaluate the impact of social support on improving self-management of type 2 diabetes mellitus[J].BMC Medical Informatics and Decision Making，2019，19（1）：197.
19	程刚，陆卫东，陈志峰，等.基于FAHP-MODM的矿井通风系统可靠性综合评价[J].中国安全生产科学技术，2018，14（2）：99-105.
	Cheng Gang，Lu Weidong，Chen Zhifeng，et al.Comprehensive evaluation on reliability of ventilation system in mine based on FAHP-MODM[J].Journal of Safety Science and Technology，2018，14（2）：99-105.
20	刘毅，蒋仲安，蔡卫，等.综采工作面粉尘运动规律的数值模拟[J].北京科技大学学报，2007（4）：351-353，362.
	Liu Yi，Jiang Zhong’an，Cai Wei，et al.Numerical simulation of the dust movement rule in fully-mechanized coal faces[J].Journal of University of Science and Technology Beijing，2007（4）：351-353，362.
21	Andrew T.High-altitude illnesses：Physiology，risk factors，prevention，and treatment[J].Rambam Maimonides Medical Journal，2011，2（1）：e0022.
22	刘睿，余建星，孙宏才，等.基于 ANP 的超级决策软件介绍与其应用[J].系统工程理论与实践， 2003（8）：141-143.
	Liu Rui，Yu Jianxing，Sun Hongcai，et al.Introduction to the ANP super decisions software and its application[J].Systems Engineering-theory & Practice，2003（8）：141-143.

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一级指标	二级指标	一级指标	二级指标
方案P	长压短抽P₁	技术效益T	有效风量率T₁
	长抽短压P₂		风量供需比T₂
	长抽长压P₃		通风阻力T₃
安全效益S	除尘效果S₁	经济效益E	购置费用E₁
	供氧效果S₂		安装费用E₂
	风流稳定性S₃		使用维护费用E₃
	风机稳定性S₄		风机效率E₄

评价指标		方案			安全效益S				技术效益T			经济效益E
评价指标		P₁	P₂	P₃	S₁	S₂	S₃	S₄	T₁	T₂	T₃	E₁	E₂	E₃	E₄
方案P	P₁				√	√	√	√	√	√	√	√	√	√	√
	P₂				√	√	√	√	√	√	√	√	√	√	√
	P₃				√	√	√	√	√	√	√	√	√	√	√
安全效益S	S₁	√	√	√		√
	S₂	√	√	√	√
	S₃	√	√	√	√	√		√	√	√
	S₄	√	√	√	√	√	√		√	√					√
技术效益T	T₁	√	√	√	√	√	√			√				√
	T₂	√	√	√	√	√	√		√					√
	T₃	√	√	√	√	√	√	√
经济效益E	E₁	√	√	√	√	√	√	√	√	√			√	√	√
	E₂	√	√	√	√	√	√	√				√		√
	E₃	√	√	√	√	√	√	√	√	√					√
	E₄	√	√	√	√	√	√	√	√	√		√	√	√

评价指标	方案P	安全效益S	技术效益T	经济效益E
方案P	0	12	9	12
安全效益S	12	8	4	1
技术效益T	9	10	2	2
经济效益E	12	16	6	9

评价指标		方案P	安全效益S	技术效益T	经济效益E
方案P	P₁	0	4	3	4
	P₂	0	4	3	4
	P₃	0	4	3	4
安全效益S	S₁	3	1	0	0
	S₂	3	1	0	0
	S₃	3	3	2	0
	S₄	3	3	2	1
技术效益T	T₁	3	3	1	1
	T₂	3	3	1	1
	T₃	3	4	0	0
经济效益E	E₁	3	4	2	3
	E₂	3	4	0	2
	E₃	3	4	2	1
	E₄	3	4	2	3

序号	重要性等级	C_ij赋值
1	i、j两元素同等重要	1
2	i元素比j元素稍重要	3
3	i元素比j元素明显重要	5
4	i元素比j元素强烈重要	7
5	i元素比j元素极端重要	9
6	i元素比j元素稍不重要	1/3
7	i元素比j元素明显不重要	1/5
8	i元素比j元素强烈不重要	1/7
9	i元素比j元素极端不重要	1/9

Ventilation Mode Optimization of Mining Face at High Altitude Based on ANP

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一级指标	二级指标	全局权重/%	综合权重/%
方案P	长压短抽P₁	17.86	46.16
	长抽短压P₂	06.78	17.51
	长抽长压P₃	14.06	36.33
安全效益S	除尘效果S₁	16.45	37.81
	供氧效果S₂	20.08	46.13
	风流稳定性S₃	02.75	06.32
	风机稳定性S₄	04.24	09.75
技术效益T	有效风量率T₁	02.23	34.70
	风量供需比T₂	03.70	57.49
	通风阻力T₃	00.50	07.82
经济效益E	购置费用E₁	04.60	40.48
	安装费用E₂	01.16	10.22
	使用维护费用E₃	03.31	29.11
	风机效率E₄	02.30	20.20

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