SHI Yu-chuan,JI Feng,FENG Wen-kai.Application of BP Neural Network in the Tunnel Rock Blasting[J].Research of Soil and Water Conservation,2007,14(05):242-244.
BP神经网络在隧道岩爆预测中的应用
- Title:
- Application of BP Neural Network in the Tunnel Rock Blasting
- Keywords:
- BP neural network; tunnel; rock burst
- 分类号:
- TP813
- 摘要:
- 西南某水电站拟修建4条引水隧洞以及2条平行交通隧道，但工程区一般埋深1 000～2 000 m，最大埋深2 525 m，地处高应力区，目前已开挖的2 000 m洞段中均发现轻微至中等的岩爆现象。因此，在深埋、长大的隧道以后开挖过程中岩爆烈度如何显得十分敏感，利用BP人工神经网络，建立了以强度脆性系数、应力系数等8个指标为要素的岩爆预测模型，对12 200 m未开挖的辅助洞段进行了预报，结果表明，该方法的预报效果较好。与地质分析判断相吻合，可用于进一步指导实践。
- Abstract:
- Four diversion tunnels and two parallel traffic tunnels to be constructed in a hydropower of Southwest,but the buried deep in the project area is 1 000～2 000 m in general,the largest is 2 525 m,which located in the high stress zone,now excavation hole of the 2 000 m are found in the low to medium rock burst phenomenon,therefore,rock burst intensity of the tunnel is very sensitive in subsequent excavation in the deep,long and big conditions,using BP artificial neural network established a burst prediction models which includes strength brittleness factor,stress factors such as elements of the eight indicators,achieved 12 200 m support for the forthcoming excavation hole of a forecast.The results showed that the effect of this forecasting methods is good,and coincide with the geological analysis judgement,which can be used for further guidance practice.
参考文献/References:
[1] (GB50287-99)水利水电工程地质勘察规范[S].
[2] 徐则明, 黄润秋.深埋特长隧道及其施工地质灾害[M].成都:西南交通大学出版社, 2000.
[3] 谭以安.模糊数学综合评判在地下洞室岩爆预测中的应用[A].第二次全国岩石力学与工程学术会议论文集[C].北京:知识出版社, 1989.
[4] 杨健, 武雄.岩爆综合预测评价方法[J].岩石力学与工程学报, 2005, 24(3):411-416.
[5] 汪培庄, 韩立岩.应用模糊数学[M].北京经济学院出版社, 1989.
[8] 唐礼忠, 王文星.一种新的岩爆倾向性指标[J].岩石力学与工程学报, 2002, 21(6):874-878.
相似文献/References:
[1]张丽,吴金亮,杨国范.基于BP神经网络的东港灌区作物需水量预测研究[J].水土保持研究,2012,19(06):207.
ZHANG Li,WU Jin-liang,YANG Guo-fan.Prediction Research for Crop Water Requirement Based on BP Neural Network in Donggang Irrigation District[J].Research of Soil and Water Conservation,2012,19(05):207.
[2]封毅,武博强,崔灵周.基于BP神经网络的台风降雨量预测研究[J].水土保持研究,2012,19(03):289.
FENG Yi,WU Bo-qiang,CUI Ling-zhou.Study on Forecasting Typhoon Rainfall Based on BP Neural Network[J].Research of Soil and Water Conservation,2012,19(05):289.
[3]刘吉平,刘佳鑫,于洋,等.不同采样尺度下土壤碱解氮空间变异性研究——以榆树市农田土壤为例[J].水土保持研究,2012,19(02):106.
LIU Ji-ping,LIU Jia-xin,YU Yang,et al.Study on Spatial Variability of Available Nitrogen in Different Sampling Scale——A Case Study on Cropland Soil in Yushu City[J].Research of Soil and Water Conservation,2012,19(05):106.
[4]孔萌,刘俊民.BP神经网络L-M优化算法在地下水动态预测中的应用[J].水土保持研究,2007,14(05):51.
KONG Meng,LIU Jun-min.Applying the BP Net work L-M Optimize Arithmetic to Simulate and Forecast the Ground Water Dynamic[J].Research of Soil and Water Conservation,2007,14(05):51.
[5]王增彬,迟恒智.基于BP神经网络的济南市建设用地规模预测[J].水土保持研究,2007,14(05):245.
WANG Zeng-bin,CHI Heng-zhi.Prediction of Urban Building Land in Jinan Based on ANN Model[J].Research of Soil and Water Conservation,2007,14(05):245.
[6]王艳,宋振柏,吴佩林.基于BP网络的高新技术产业用地适宜性评价[J].水土保持研究,2008,15(04):248.
WANG Yan,SONG Zhen-bai,WU Pei-lin.Land Suitability Evaluation of High and New Technology Industry Based on BP Network[J].Research of Soil and Water Conservation,2008,15(05):248.
[7]刘登峰,齐实,韩小杰,等.缙云山不同土地利用类型地表径流水质评价[J].水土保持研究,2009,16(01):126.
LIU Deng-feng,QI Shi,HAN Xiao-jie,et al.Surface Runoff Quality Evaluation of Several Land Uses in Jinyun Moutain[J].Research of Soil and Water Conservation,2009,16(05):126.
[8]刘建,刘丹.岩溶隧道建设引起的地下水环境负效应研究——以铜锣山隧道为例[J].水土保持研究,2009,16(03):268.
LIU Dan,LIU Dan.Study on Groundwater Negative Effects Resulted by Tunnel Construction in Karst Areas—A Case Study of Tongluoshan Tunnel[J].Research of Soil and Water Conservation,2009,16(05):268.
[9]蔡明科,胡国杰,许义和.基于人工神经网络的宝鸡市市区地下水调控方案研究[J].水土保持研究,2010,17(05):176.
CAI Ming-ke,HU Guo-jie,XU Yi-he.Study on Regulation Schemes in the Urban Area of Baoji City with Artificial Neural Network[J].Research of Soil and Water Conservation,2010,17(05):176.
[10]武开福.基于灰色关联度与BP神经网络模型的日参考作物腾发量预测[J].水土保持研究,2011,18(02):237.
WU Kai-fu.Discuss on Daily Crop Evapotranspiration Forecast Based on Gray Relation Analysis and BP Neural Network[J].Research of Soil and Water Conservation,2011,18(05):237.
备注/Memo
收稿日期:2006-7-22。
作者简介:石豫川（1965- ），男，副教授，博士，主要从事岩土及工程地质研究。