摘要
AHP法是煤层底板突水预测预报的关键技术之一,但传统基于"1~9"标度的AHP法往往存在一致性效果不够理想等问题.通过对AHP法的改进研究,提出了基于"10/10~18/2"标度的改进AHP法型脆弱性指数法评价技术.以成庄矿3~#、9~#和15~#煤层底板奥灰突水脆弱性评价为例,在建立各主控因素专题层图基础上,应用基于"10/10~18/2"新标度的改进AHP法,确定了各主控因素的权重;进一步建立了煤层底板奥灰突水的脆弱性评价模型,得出了各煤层脆弱性评价分区.研究表明,改进的AHP法构建的判断矩阵具有较好的一致性;通过与传统突水系数法评价结果对比可知,基于GIS的改进AHP型脆弱性指数法评价能够真实反映多因素影响下煤层底板突水的非线性动力过程,评价结果更为吻合实际.
The AHP method is one of the key technologies in predicting coal seam floor water inrush. But, the traditional AHP method, which is based on 1--9 scale, often has some problems. For example, the consistency effect is not ideal. Therefore, through the research on these problems, the technique of the improved AHP vulnerable index method, which is based on 10/ 10--18/2 scale, was put forward. Then, the vulnerability evaluation of the No. 3, 9 and 15 coal in Chengzhuang eoalmine was taken as an example. Firstly, based on the establishment of the thematic layers diagrams of eight main factors, the weight of each main factors was determined using the improved AHP method. Then, the vulnerability evaluation model of the floor water inrush from the Ordovician limestone aquifer was constructed. Finally, the vulnerability zoning of each part in the study area of the No. 3, 9 and 15 coal mine were obtained. The results showed that the judgment matrix constructed by the improved AHP method has better consistency effect. Furthermore, compared with the results of the traditional water inrush coefficient meth- od, the results of the improved AHP vulnerability index method, which can truly reflect the nonlinear dynamic process of the floor water inrush under multi-factor affection, are more consistent with the actual.
作者
刘守强
武强
曾一凡
宫厚健
李哲
Liu Shouqiang Wu Qiang Zeng Yifan Gong Houjian Li Zhe(National Engineering Research Center of Coal Mine Water Hazard Controlling, China University of Mining & Technology, Beijing 100083, China)
出处
《地球科学(中国地质大学学报)》
EI
CSCD
北大核心
2017年第4期625-633,共9页
Earth Science-Journal of China University of Geosciences
基金
国家自然科学基金项目(Nos.41272276
41602262)
高等学校博士学科点专项科研基金项目(No.20130023120018)
国家重点研发计划重点专项项目(No.2016YFC0801801)