节点文献

模糊综合评判法预测煤与瓦斯突出强度的研究

Study on way of predicting coal and gas outburst scale by fuzzy synthesis evaluation

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 蔡成功景国勋

【Author】 CAI Cheng-gong, JING Guo-xun (Department of Resource and Material Engineering, Jiaozuo Institute of Technology, Jiaozuo 454000, Henan, China)

【机构】 焦作工学院资源与材料工程系焦作工学院资源与材料工程系 河南焦作454000河南焦作454000

【摘要】 依据统计数据和专家经验 ,应用层次分析法确定各影响因素对突出强度的贡献度权重 ,采用定性数据定量化方法确定各因素的隶属度 ,采用二级模糊综合评判方法和“加权平均型”评判数学模型 ,建立了煤与瓦斯突出强度预测模糊综合评判方法 ,实现了煤与瓦斯突出强度的定量预测。

【Abstract】 Based on a great many statistical data, the present paper has analyzed the complicated relations between the coal and gas outburst scales and various factors, such as mining depth, tunnel types, geological structures, outburst signs, coal seam thickness and the ways of exploitation, thus finding the general regularities of the outburst scales. As is known, once the hierarchy analysis model of coal and gas outburst scales is established and the weight of each factor contribution grade for the outburst scales has been accounted for through the hierarchy analysis process. As the membership grades are subordinated to the outburst scales: large scales (scales ≥500 T), medium-sized (scales between 100 T to 500 T) and small ones (scales <100 T) are determined by the methods of the quantitative analysis on the qualitative data, a two-stage fuzzy synthesis evaluation method and the average weight mathematical model, i.e. the method for predicating coal and gas outburst scales, can be set up so that the validation for the quantitative predication on coal and gas outburst scales in Limin mine and Hongshandian mine of Lianshao Coal (Group) Co. can be actualized. The methods are expediently developed into computer managing system and applied to daily technique management in coalmines of coal and gas outburst. The results of trial application in this research have lent a highly important means for preventing coal and gas outbursts.

  • 【文献出处】 安全与环境学报 ,Journal of Safety and Environment , 编辑部邮箱 ,2004年02期
  • 【分类号】TD713
  • 【被引频次】39
  • 【下载频次】297
节点文献中: 

本文链接的文献网络图示:

本文的引文网络