|本期目录/Table of Contents|

[1]王超,李岳峰,张成良.基于不同指标无量纲化方法的岩爆预测模型优选[J].中国安全生产科学技术,2020,16(2):24-29.[doi:10.11731/j.issn.1673-193x.2020.02.004]
　WANG Chao,LI Yuefeng,ZHANG Chengliang.Optimization of rockburst prediction model based on different index dimensionless methods[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(2):24-29.[doi:10.11731/j.issn.1673-193x.2020.02.004]
点击复制

基于不同指标无量纲化方法的岩爆预测模型优选
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
16
期数:
2020年2期
页码:
24-29
栏目:
学术论著
出版日期:
2020-02-29

文章信息/Info

Title:
Optimization of rockburst prediction model based on different index dimensionless methods
文章编号:
1673-193X(2020)-02-0024-06
作者:
王超; 李岳峰; 张成良
(1.昆明理工大学 国土资源工程学院，云南 昆明 650093;
2.云南省中-德蓝色矿山与特殊地下空间开发利用重点实验室，云南 昆明 650093)
Author(s):
WANG Chao;  LI Yuefeng;  ZHANG Chengliang
(1.Faculty of Land Resources Engineering,Kunming University of Science and Technology,Kunming Yunnan 650093,China;
2.Yunnan Key Laboratory of SinoGerman Blue Mining and Utilization of Special Underground Space,Kunming Yunnan 650093,China)
关键词:
无量纲化; 岩爆等级; 预测模型; 距离判别法; 对比研究; 优选
Keywords:
dimensionless;  rockburst grade;  prediction model;  distance discriminant method;  comparative study;  optimization
分类号:
X936;TU457
DOI:
10.11731/j.issn.1673-193x.2020.02.004
文献标志码:
A
摘要:
为研究不同指标无量纲化方法对岩爆等级预测模型精度的影响，提高岩爆预测准确率，选取应力系数、脆性系数和弹性能量指数作为预测指标。基于104组岩爆实例大样本数据，采用统一极差处理法、差异化极差处理法、平均化处理法和归一化处理法4种指标无量钢化方法，对预测指标的原始数据进行处理，建立不同的岩爆预测距离判别模型并进行工程实例应用。研究结果表明：基于平均化处理法的岩爆预测模型的回判准确率高达97.1%；对不同矿山、隧道和水电站的6个工程实例的预测结果符合实际情况，说明其是一种准确率高、方便实用的岩爆预测模型。
Abstract:
In order to study the influence of different index dimensionless methods on the accuracy of prediction models on the rockburst grades,and improve the accuracy of rockburst prediction,the stress coefficient,brittleness coefficient and elastic energy index of rock were chosen as the prediction indexes.Based on 104 groups of large sample data of rockburst examples,the original data of prediction indexes were processed by using four types of index dimensionless methods including the unified extreme value processing method,differentiated extreme value processing method,averaging processing method and normalized processing method.Different distance discriminant models of rockburst prediction were established and applied in the engineering cases.The results showed that the accuracy of rockburst prediction model based on the averaging processing method reached as high as 97.1%,and the prediction results on six engineering cases of different mines,tunnels and hydroelectric power stations were completely consistent with the actual situation,which indicated that it is a rockburst prediction model with high accuracy,convenience and practicability.

参考文献/References:

［1］藕明江,周宗红,王友新,等.不同卸荷速率条件下岩爆碎屑破坏特征分析［J］.中国安全生产科学技术,2017,13(11):97-103. OU Mingjiang,ZHOU Zonghong,WANG Youxin,et al.Analysis on failure characteristics of rock burst fragments under different unloading rate condition［J］.Journal of Safety Science and Technology,2017,13(11):97-103.
［2］王元汉,李卧东,李启光,等.岩爆预测的模糊数学综合评判方法［J］.岩石力学与工程学报,1998,17(5):493-501. WANG Yuanhan,LI Wodong,LI Qiguang,et al.Comprehensive method for estimating rock burst with FUZZY［J］.Chinese Journal of Rock Mechanics and Engineering,1998,17(5):493-501.
［3］吴顺川,张晨曦,成子桥.基于PCA-PNN原理的岩爆烈度分级预测方法［J］.煤炭学报,2019,44(9):2767-2776. WU Shunchuan,ZHANG Chenxi,CHENG Ziqiao.Prediction method of rockburst intensity classification based on PCA-PNN principle ［J］.Journal of China Coal Society,2019,44(9):2767-2776.
［4］陈祥,孙进忠,张杰坤,等.岩爆的判别指标和分级标准及可拓综合判别方法［J］.土木工程学报,2009,42(9):82-88. CHEN Xiang,SUN Jinzhong,ZHANG Jiekun,et al.Judgment indexes and classification criteria of rock-burst with the extension judgment method ［J］.China Civil Engineering Journal,2009,42(9):82-88.
［5］徐飞,徐卫亚.岩爆预测的粒子群优化投影寻踪模型［J］.岩土工程学报,2010,32(5):718-723. XU Fei,XU Weiya.Projection pursuit model based on particle swarm optimization for rock burst prediction ［J］.Chinese Journal of Geotechnical Engineering,2010,32(5):718-723.
［6］邱道宏,李术才,张乐文,等.基于模型可靠性检查的QGA-SVM岩爆倾向性分类研究［J］.应用基础与工程科学学报,2015,23(5):981-991. QIU Daohong,LI Shucai,ZHANG Lewen,et al.Research on QGASVM rock burst orientation classification based on model reliability examination ［J］.Journal of Basic Science and Engineering,2015,23(5):981-991.
［7］朱家锐,何世林,胡万宏,等.基于熵权的模糊物元模型在岩爆倾向性评价中的应用［J］.湖南科技大学学报(自然科学版),2010,25(2):10-13. ZHU Jiarui,HE Shilin,HU Wanhong,et al.Application of fuzzy matter-element model based on coefficients of evaluation in rock burst［J］.Journal of Hunan University of Science & Technology (Natural Science Edition),2010,25(2):10-13.
［8］李绍红,王少阳,朱建东,等.基于权重融合和云模型的岩爆倾向性预测研究［J］.岩土工程学报,2018,40(6):1075-1083. LI Shaohong,WANG Shaoyang,ZHU Jiandong,et al.Prediction of rock burst tendency based on weight fusion and improved cloud model ［J］.Chinese Journal of Geotechnical Engineering,2018,40(6):1075-1083.
［9］田杰,王威,郭小东,等.基于分形插值模型的岩爆预测研究［J］.北京工业大学学报,2012,38(4):481-485. TIAN Jie,WANG Wei,GUO Xiaodong,et al.Prediction of rock burst based on the fractal interpolation model ［J］.Journal of Beijing University of Technology,2012,38(4):481-485.
［10］张天余,李建朋,廖万辉.突变级数法在隧道岩爆等级预测中应用［J］.公路,2018(9):316-320. ZHANG Tianyu,LI Jianpeng,LIAO Wanhui.Application of catastrophe progression method in tunnel rockburst prediction ［J］.Highway,2018(9):316-320.
［11］王旷,李夕兵,马春德,等.基于改进的RS-TOPSIS模型的岩爆倾向性预测［J］.黄金科学技术,2019(27):80-88. WANG Kuang,LI Xibing,MA Chunde,et al.Rock-burstproneness prediction based on improved RS-TOPSIS model［J］.Gold Science and Technology,2019(27):80-88.
［12］宫凤强,李夕兵.岩爆发生和烈度分级预测的距离判别方法及应用［J］.岩石力学与工程学报,2006,26(5):1012-1018. GONG Fengqiang,LI Xibing.Distance discrimination method for rockburst occurrence and intensity classification prediction and its application ［J］.Chinese Journal of Rock Mechanics and Engineering,2006,26(5):1012-1018.
［13］付玉华,董陇军.岩爆预测的Bayes判别模型及应用［J］.中国矿业大学学报,2009,38(4):528-533. FU Yuhua,DONG Longjun.Bayes discriminant analysis model and its application to the prediction and classification of rockburst［J］.Journal of China University of Mining and Technology,2009,38(4):528-533.
［14］白云飞,邓建,董陇军,等.深部硬岩岩爆预测的FDA模型及其应用［J］.中南大学学报(自然科学版),2009,40(5):1417-1422. BAI Yunfei,DENG Jian,DONG Longjun,et al.FDA model of rock burst prediction and its application in deep hard rock engineering［J］.Journal of Central South University (Science and Technology),2009,40(5):1417-1422.
［15］周科平,林允,胡建华,等.基于熵权-正态云模型的岩爆烈度分级预测研究［J］.岩土力学,2016,37(S1):596-602. ZHOU Keping,LIN Yun,HU Jianhua,et al.Grading prediction of rockburst intensity based on entropy and normal cloud model［J］.Rock and Soil Mechanics,2016,37(S1):596-602.

相似文献/References:

备注/Memo

备注/Memo:
收稿日期： 2019-11-03
* 基金项目： 国家自然科学基金项目（51934003,51864023）；云南省高校深地资源开发科技创新团队支持计划项目（201809）；昆明理工大学分析测试基金项目（2017T20130130）
作者简介： 王超，博士，讲师，主要研究方向为矿山安全与岩石力学。
通信作者： 张成良，博士，副教授，主要研究方向为岩土与爆破工程。
更新日期/Last Update: 2020-03-16