基于变权贝叶斯理论的岩爆预测模型及应用

胡澳玲; 王文杰; 杨金维; 寇永渊; 郁标

doi:10.20174/j.JUSE.2024.06.09

地下空间与工程学报 >

2024 , Vol. 20 >Issue 6: 1837 - 1845

DOI: https://doi.org/10.20174/j.JUSE.2024.06.09

理论与试验研究

基于变权贝叶斯理论的岩爆预测模型及应用

胡澳玲 ,
王文杰 ,
杨金维 ,
寇永渊 ,
郁标

展开

1.武汉科技大学资源与环境工程学院,武汉 430081;
2.金川集团股份有限公司二矿区,甘肃金昌 737100

胡澳玲(1999—),女,辽宁沈阳人,硕士生,主要从事地压灾害风险评估方面的研究工作。E-mail:2945900550@qq.com

王文杰(1978—),男,甘肃庆阳人,博士,教授,主要从事金属矿床地下开采工艺、巷道支护及地压控制方面研究。E-mail:wangwenjie@wust.edu.cn

收稿日期: 2024-03-21

网络出版日期: 2025-01-03

基金资助

国家自然科学基金项目(51974206);湖北省安全生产专项资金科技项目(KJZX202007007)

收起

Prediction Model of Rockburst Based on Variable Weight Bayesian and Its Application

Hu Aoling ,
Wang Wenjie ,
Yang Jinwei ,
Kou Yongyuan ,
Yu Biao

Expand

1. School of Resources and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, P. R. China;
2. No. 2 Mine Area, Jinchuan Group Co., Ltd., Jinchang, Gansu 737100, P. R. China

Received date: 2024-03-21

Online published: 2025-01-03

Fold

摘要

岩爆灾害对地下矿山安全开采影响较大,准确可靠的岩爆灾害预测对安全生产意义重大。为了准确有效地进行岩爆灾害预测,首先,选取应力系数、脆性系数、弹性能量指数以及岩体完整性系数作为预测指标,建立了岩爆预测指标体系;其次,在层次分析法(AHP)、改进CRITIC法以及距离函数判别法确定综合常权重基础上,利用变权理论对常权重进行动态修正;然后,引入有效度对最大后验概率原则进行改进,构建了变权贝叶斯岩爆烈度等级预测模型。最后,选取15组岩爆工程实例进行模型可靠性验证和准确率对比,并采用该模型对金川二矿1 000 m水平中段进行了岩爆预测。研究表明:变权贝叶斯岩爆预测模型准确率可达93%;金川二矿1 000 m水平中段岩爆烈度等级为无~轻微,岩爆危害较小,预测结果与实际相符,可为岩爆防治提供依据。

关键词： 岩爆烈度等级; 距离函数; 变权理论; 贝叶斯理论; 金川二矿

本文引用格式

胡澳玲 , 王文杰 , 杨金维 , 寇永渊 , 郁标 . 基于变权贝叶斯理论的岩爆预测模型及应用[J]. 地下空间与工程学报, 2024 , 20(6) : 1837 -1845 . DOI: 10.20174/j.JUSE.2024.06.09

Abstract

Rockburst has a large impact on the safe mining of underground mines, and accurate and reliable prediction of rockburst is of great significance to safe production. In order to accurately and effectively predict rockburst, firstly, the stress coefficient, brittleness coefficient, elastic energy index, and integrity coefficient are selected as prediction indicators, and the rockburst prediction index system is established. Secondly, based on the hierarchical analysis method (AHP), improved CRITIC method, and the distance function discriminant method for determining the integrated constant weight, the constant weight is dynamically corrected using the variable weight theory. Then, the effectiveness is introduced to modify the principle of maximum posterior probability, and a Bayesian rockburst intensity grade prediction model with variable weight is constructed. Finally, 15 groups of rockburst engineering examples are selected to verify the reliability and compare the accuracy of the model, and the model is used to predict the rockburst in the middle section of the 1 000 m level of Jinchuan No.2 Mine. The research results show that the accuracy of the Bayesian rockburst prediction model with variable weight can reach 93%. The rockburst intensity grade in the middle section of the 1 000 m level of Jinchuan No. 2 Mine is none to slight, and the harm of rockburst is relatively small. The prediction results are in line with the actual situation, which can provide a basis for rockburst prevention and control.

Key words： rockburst intensity grade; distance function; variable weight; Bayesian theory; Jinchuan No.2 Mine

参考文献

[1] 谢和平.深部岩体力学与开采理论研究进展[J]. 煤炭学报, 2019, 44(5): 1283-1305. (Xie Heping. Research review of the state key research development program of China: Deep rock mechanics and mining theory[J]. Journal of China Coal Society, 2019, 44(5): 1283-1305. (in Chinese))
[2] 张传庆,卢景景,陈珺,等.岩爆倾向性指标及其相互关系探讨[J]. 岩土力学, 2017, 38(5): 1397-1404. (Zhang Chuanqing, Lu Jingjing, Chen Jun, et al. Discussion on rock burst proneness indexes and their relation[J]. Rock and Soil Mechanics, 2017, 38(5): 1397-1404. (in Chinese))
[3] 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(5): 15-23. (Wang Yuanhan, Li Wodong, Li Qiguang, et al. Method of fuzzy comprenhensive evaluations for and rockburst prediction[J]. Chinese Journal of Rock Mechanics and Engineering, 1998(5): 15-23. (in Chinese))
[4] 赵浩杨,石广斌,杨振宏,等.基于组合赋权-改进集对分析的岩爆倾向性预测研究[J]. 金属矿山, 2021(5): 71-77. (Zhao Haoyang, Shi Guangbin, Yang Zhenhong, et al. Study on rockburst tendency prediction based on combined weighting-improved set pair analysis[J]. Metal Mine, 2021(5): 71-77. (in Chinese))
[5] 罗磊,曹平.深部巷道岩爆加权距离判别法模型的分析和应用[J]. 中南大学学报:自然科学版, 2012, 43(10): 3971-3975. (Luo Lei, Cao Ping. Model of weighted distance discriminant analysis and application for deep roadway[J]. Journal of Central South University:Science and Technology, 2012, 43(10): 3971-3975. (in Chinese))
[6] 张徐琛,刘晓丽,王恩志,等.基于组合权重-理想点法的应变型岩爆五因素预测分级[J]. 岩土工程学报, 2017, 39(12): 2245-2252. (Zhang Xuchen, Liu Xiaoli, Wang Enzhi, et al. Prediction and classification of strain mode rockburst based on five-factor criterion and combined weight-ideal point method[J]. Chinese Journal of Geotechnical Engineering, 2017, 39(12): 2245-2252. (in Chinese))
[7] 周航,陈仕阔,张广泽,等.基于功效系数法和地应力场反演的深埋长大隧道岩爆预测研究[J]. 工程地质学报, 2020, 28(6):1386-1396.(Zhou Hang, Chen Shikuo,Zhang Guangze, et al. Efficiency coefficient method and ground stress field inversion for rockburst predicition in deep and long tunnel[J]. Journal of Engineering Geology, 2020, 28(6): 1386-1396. (in Chinese))
[8] 董源,裴向军,张引,等.基于组合赋权-云模型理论的岩爆预测研究[J].地下空间与工程学报, 2018, 14(增1): 409-415.(Dong Yuan, Pei Xiangjun, Zhang Yin, et al. Prediction of rock burst-based on combination weighting and cloud model theory[J]. Chinese Journal of Underground Space and Engineering, 2018,14(Supp.1): 409-415. (in Chinese))
[9] 马佳骥,马春驰,曾俊,等.基于LSTM多变种模型的岩爆微震参数预测研究[J].地下空间与工程学报,2022,18(5):1481-1494.(Ma Jiaji, Ma Chunchi,Zeng Jun, et al. Research on the prediction of rockburst microseismic parameters based on LSTM multivariate model[J]. Chinese Journal of Underground Space and Engineering, 2022, 18(5): 1481-1494. (in Chinese))
[10] 付自国,李化,邓建辉,等.自组织特征映射神经网络在岩爆分级预测中的应用[J].地下空间与工程学报, 2023, 19(1): 334-342.(Fu Ziguo, Li Hua,Deng Jianhui, et al. Application of self-organizing feature map in rockburst classification[J]. Chinese Journal of Underground Space and Engineering, 2023, 19(1): 334-342. (in Chinese))
[11] 陈则黄,李克钢,李明亮,等.基于PCA-SOFM模型的岩爆烈度等级预测[J].地下空间与工程学报,2022,18(增2):934-942,951.(Chen Zehuang,Li Kegang,Li Mingliang,et al.Prediction of rockburst intensity based on PCA-SOFM Model[J].Chinese Journal of Underground Space and Engineering,2022,18(Supp.2):934-942,951.(in Chinese))
[12] 刘剑,周宗红.基于修正散点图矩阵与随机森林的岩爆等级预测[J].有色金属工程, 2022, 12(3): 120-128. (Liu Jian, Zhou Zonghong. Rockburst grade predictionin based on modified scatter graph matrixn and random forest[J]. Nonferrous Metals Engineering, 2022, 12(3): 120-128. (in Chinese))
[13] 殷欣,刘泉声,王心语,等.基于组合赋权和属性区间识别理论的岩爆烈度分级预测模型[J]. 煤炭学报, 2020, 45(11): 3772-3780.(Yin Xin,Liu Quansheng,Wang Xinyu, et al. Prediction model of rockburst intensity classification based on combined weighting and attribute interval recognition theory[J]. Journal of China Coal Society, 2020, 45(11): 3772-3780. (in Chinese))
[14] 刘磊磊,张绍和,王晓密.基于物元矩阵和理想点法的岩爆烈度预测[J].地下空间与工程学报,2016,12(1):205-212.(Liu Leilei,Zhang Shaohe,Wang Xiaomi.Prediction of rockburst intensity based on matter-element matrix and ideal point method[J].Chinese Journal of Underground Space and Engineering,2016,12(1):205-212.(in Chinese))
[15] 李明亮,李克钢,秦庆词,等.基于改进组合赋权-TOPSIS法的岩爆倾向性评判模型[J]. 中国安全生产科学技术, 2020, 16(3): 74-80.(Li Mingliang,Li Kegang,Qin Qingci,et al. Judgment model of rock burst tendency based on improved combination weighting-TOPSIS method[J]. Journal of Safety Science and Technology, 2020, 16(3): 74-80.(in Chinese))
[16] 黄建,夏元友,吝曼卿.基于改进组合赋权的岩爆多维云模型预测研究[J]. 中国安全科学学报, 2019, 29(7): 26-32.(Huang Jian,Xia Yuanyou, Lin Manqing, et al. Study on prediction of rock burst by multi-dimensional cloud model based on improved combined weight[J]. China Safety Science Journal, 2019, 29(7): 26-32. (in Chinese))
[17] 张晨,王清,陈剑平,等.金沙江流域泥石流的组合赋权法危险度评价[J]. 岩土力学, 2011, 32(3): 831-836.(Zhang Chen,Wang Qing,Chen Jianping, et al. Evaluation of debris flow risk in Jinsha River based on combined weight process[J]. Rock and Soil Mechanics, 2011, 32(3): 831-836. (in Chinese))
[18] 李韶慧,周忠发,但雨生,等.基于组合赋权贝叶斯模型的平寨水库水质评价[J].水土保持通报, 2020, 40(2): 211-217.(Li Shaohui,Zhou Zhongfa, Dan Yusheng, et al. Water quality evaluation of Pin Zhai reservoir based on combined weighted Bayesian model[J]. Bulletin of Soil and Water Conservation, 2020, 40(2): 211-217. (in Chinese))
[19] 徐健,吴玮,黄天寅,等.改进的模糊综合评价法在同里古镇水质评价中的应用[J]. 河海大学学报:自然科学版,2014,42(2):143-149.(Xu Jian, Wu Wei, Huang Tianyin, et al. Application of improved fuzzy comprehensive evaluation to water quality evaluation in Tongli Town[J]. Journal of Hohai University:Natural Sciences, 2014, 42(2): 143-149. (in Chinese))
[20] 王羽,许强,柴贺军,等.工程岩爆灾害判别的RBF-AR耦合模型[J].吉林大学学报:地球科学版, 2013, 43(6): 1943-1949, 1965.(Wang Yu, Xu Qiang, Chai Hejun, et al. Rock burst prediction in deep shaft based on RBF-AR model[J]. Journal of Jilin University(Earth Science Edition), 2013, 43(6): 1943-1949, 1965. (in Chinese))
[21] 李宗坤,莫向明,葛巍,等.基于变权集对-可拓耦合模型的溃坝后果综合评价[J]. 工程科学与技术, 2022, 54(5): 64-71. (Li Zongkun, Mo Xiangming, Ge Wei, et al. Comprehensive evaluation of dam-break consequences based on variable weight set pair-extenics coupling model[J]. Advanced Engineering Scineces, 2022, 54(5): 64-71. (in Chinese))
[22] 衣永亮,曹平,蒲成志.金川深部典型岩石岩爆倾向性多因素综合评判[J]. 科技导报, 2010, 28(2): 76-80. (Yi Yongliang, Cao Ping, Pu Chengzhi. Multi-factorial comprehensive estimation for Jinchuan's deep typical rockburst tendency[J]. Science & Technology Review, 2010, 28(2): 76-80. (in Chinese))

Options

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献