Hazard degree identification of goafs based on scale effect of structure by RS-TOPSIS method
来源期刊：中南大学学报(英文版)2015年第2期
论文作者：胡建华 SHANG Jun-long(尚俊龙) ZHOU Ke-ping(周科平) CHEN Yi-kai(陈宜楷) NING Yu-lin(甯榆林) LIU Lang(刘浪) Mohammed M. Aliyu
文章页码：684 - 692
Key words：goaf; RS-TOPSIS method; hazard degree; scale effect
Abstract: In order to precisely predict the hazard degree of goaf (HDG), the RS-TOPSIS model was built based on the results of expert investigation. to evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set (RS) theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western china, whose indexes parameters were measured by cavity monitoring system (CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades’ typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution (TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified. Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement, while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.
HU Jian-hua(胡建华)1, SHANG Jun-long(尚俊龙)1, 3, ZHOU Ke-ping(周科平)1, CHEN Yi-kai(陈宜楷)1, NING Yu-lin(甯榆林)1, LIU Lang(刘浪)1, 2, Mohammed M. Aliyu3
(1. School of Resources and Safety Engineering, Central South University, Changsha 410083, China;
2. Energy School, Xi’an University of Science and Technology, Xi’an 710054, China;
3. School of Earth and Environment, University of Leeds, Leeds LS2 9JT, United Kingdom)
Abstract:In order to precisely predict the hazard degree of goaf (HDG), the RS-TOPSIS model was built based on the results of expert investigation. to evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set (RS) theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western china, whose indexes parameters were measured by cavity monitoring system (CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades’ typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution (TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified. Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement, while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.
Key words:goaf; RS-TOPSIS method; hazard degree; scale effect
