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黄金科学技术 ›› 2020, Vol. 28 ›› Issue (3): 457-464.doi: 10.11872/j.issn.1005-2518.2020.03.183

• 采选技术与矿山管理 • 上一篇    

基于熵权模糊法的高海拔矿井风机性能影响因素分析

宋品芳(),李孜军(),李蓉蓉,赵淑琪,徐宇   

  1. 中南大学资源与安全工程学院,湖南 长沙 410083
  • 收稿日期:2019-11-15 修回日期:2020-05-19 出版日期:2020-06-30 发布日期:2020-07-01
  • 通讯作者: 李孜军 E-mail:1466510358@qq.com;zijunli@csu.edu.cn
  • 作者简介:宋品芳(1996-),女,广西河池人,硕士研究生,从事矿井通风和安全科学理论研究工作。1466510358@qq.com
  • 基金资助:
    国家重点研发计划项目“高海拔高寒地区矿井通风安全保障技术”(2018YFC0808404);中南大学研究生自主探索创新项目“高海拔高寒地区矿井风机通风效能调控方法与技术研究”(2019zzts679)

Analysis of Factors Influencing the Performance of High Altitude Mine Fan Based on Entropy Weight Fuzzy Method

Pinfang SONG(),Zijun LI(),Rongrong LI,Shuqi ZHAO,Yu XU   

  1. School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China
  • Received:2019-11-15 Revised:2020-05-19 Online:2020-06-30 Published:2020-07-01
  • Contact: Zijun LI E-mail:1466510358@qq.com;zijunli@csu.edu.cn

摘要:

针对高海拔矿井风机性能影响因素具有复杂性、模糊性及不确定性的问题,在构建高海拔矿井风机性能评估指标体系的基础上,运用熵权法对各指标赋予权重,建立熵权模糊综合评估模型,实现高海拔矿井风机性能影响因素的有效评估和排序。以云南迪庆某矿山为例进行实证研究,结果表明:一级指标根据所占权重大小排序为风机结构>环境条件>管理因素>其他因素;二级指标中空气密度、叶片个数和叶片安装角度等6个指标对风机性能影响程度较大,而空气温度和导流叶个数等4个指标对矿井风机性能影响程度较小。研究验证了熵权模糊综合评估方法在解决高海拔矿井风机性能影响因素评估问题中的可靠性。

关键词: 高海拔矿井, 矿井风机, 风机性能, 指标体系, 信息熵理论, 熵权模糊综合评价法

Abstract:

Mine fan is an indispensable mechanical equipment in mine production,but its performance index in actual operation in the high altitude areas is far lower than the performance standard when it leaves the factory,that is,the problem of fan efficiency reduction occurs.Therefore,selecting a scientific and reasonable method to evaluate the factors affecting the performance of mine fans at high altitude is not only the basis for the selection of mine fans in the high altitude areas,but also the key factor to realize the performance optimization of mine fans in the high altitude areas.In view of the complexity,ambiguity and uncertainty of the factors influencing the performance of mine fans in the high altitude areas,the high-altitude mine fans performance evaluation index system consisting of 4 first-level indexes and 21 second-level indexes was established.On the basis of this evaluation index system of the performance of mine fans in the high-altitude areas,the paper gave each evaluation index weight by using the information entropy theory,thus,the fuzzy comprehensive evaluation model based on entropy weight method was set up.Through the use of the model,the effective evaluation and ranking of the factors influencing the performance of mine fans in the high-altitude areas was accomplished.Taking a mine in Diqing,Yunnan Province as an example for empirical,the analysis results show that the first-level indexes are ranked from the largest to the smallest according to their weight,that is fan structure,environmental conditions,management factors,other factors.Among the second-level indexes,six indexes have a great influence on fan performance.They are air density,the number of blades,blade installation angle,blade thickness,professional training and fan installation form.Moreover,four indexes have a small influence on the performance of the mine fan.They are air temperature,the number of guide blades,supervision of mine fans and selection of fan installation location.In addition,the results in this paper verify the reliability of the fuzzy comprehensive evaluation method on the basis of entropy weight in solving the problem of evaluating the factors influencing the performance of mine fans in the high-altitude areas is verified.These results also provide more solutions for the analysis of the factors influencing the performance of high-altitude mine fans.The results can provide a scientific theoretical basis for the reasonable selection and optimization design of mine fans in the high altitude areas.

Key words: high altitude mines, mine fan, fan performance, index system, information entropy theory, entropy weight fuzzy comprehensive evaluation method

中图分类号: 

  • X936

图1

高海拔矿井风机性能评估指标体系"

表1

各评估指标调研结果"

一级指标二级指标调研结果(投票)/票
极大较大中等较小极小
环境条件U1大气压力U1125171800
空气密度U123915600
相对湿度U1311192820
空气温度U1412252030
风机结构U2叶片个数U2131171200
叶片厚度U222922900
叶片安装角度U233519600
叶顶形态U2418251610
叶顶径向间隙U2515182160
轮毂比U2618221820
导流叶个数U2721216246
导流叶曲率半径U2842717102
导流体形状U2941327160
导流体长度U21011120235
出风口直径U21117221830
集流器形状U21216241730
管理因素U3保养维修U315222850
监察监管U324242660
专业培训U3316232100
其他因素U4风机安装形式U4111232150
风机安装位置U429262140
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