基于MIV的抛掷爆破影响因子权重分析
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摘要
以某露天矿为示范区,对训练样本中的自变量分别加减某个比率,构成两个新的训练样本,利用新训练样本和已训练好的神经网络,获取模拟仿真结果.计算两个训练样本模拟仿真值的差及其平均值,该平均值即为各输入参数的MIV值;以MIV值为评价依据,研究了各输入参数对最远抛掷距离、抛掷率、松散系数的影响权重;对比分析了不同MIV调节率下,各输入参数影响的权重变化情况,并应用2009-2010年实际爆破观测数据进行了相关实验.结果表明:台阶高度对最远抛掷距离、抛掷率、松散系数影响最大,其权重值在0.3~0.4之间;台阶高度与抛掷率呈正相关,与最远抛掷距离、松散系数呈负相关;平均炸药单耗对抛掷率的影响较为显著,其权重值为0.2左右,炸药单耗与抛掷率呈正相关.
This research takes an open-pit mine as a case in point,and independent variable of trained sample plus or minus a ratio constitute two new training samples.Using new training sample and the trained neurtal network is to obtain the simulation results,and calculate the difference of simulation values of the two trained samples and their average values.Those average values are MIV values of input references.The weights of input reference variables effecting on max cast distance,cast blasting ratio,coefficient of volumetric expansion are studied according to MIV values.The changing trends of input reference variables′ weights are investigated under the condition of comparative analysis of different MIV ratios.The experiment is done by using of cast blasting surveying data of some open pit during 2009-2010.The results indicate: bench height is the most important factor to affect on the prediction values of max cast distance,cast blasting ratio,coefficient of volumetric expansion.Powers of bench height ranges from 0.3 to 0.4.Bench height is positive correlation with cast blasting ratio,and is negative correlation with max cast distance and coefficient of volumetric expansion.Average explosive charge is more important factor affecting on the result of cast blasting ratio,and weight of average explosive charge is about 0.2.Average explosive charge is positive correlation with cast blasting ratio.
引文
[1]王忠强,张瑞新,张勇,等.拉斗铲作业实体高台阶安全稳定性研究[J].中国矿业大学学报,2010,39(2):185-189.WANG Zhong-qiang,ZHANG Rui-xin,ZHANGYong,et al.A study of the safety and stability of ahigh solid bench used in dragline works[J].Journalof China University of Mining&Technology,2010,39(2):185-189.
    [2]张幼蒂,傅洪贤,王启瑞,等.抛掷爆破与剥离台阶开采参数分析:露天矿倒堆剥离开采方法(Ⅳ)[J].中国矿业大学学报,2003,32(1):27-30.ZHANG You-di,FU Hong-xian,WANG Qi-rui,etal.Casting blast and analysis of mining parameters ofstripping bench:technical paper series for open castmethod in surface mine(Ⅳ)[J].Jouranl of China U-niversity of Mining&Technology,2003,32(1):27-30.
    [3]潘井澜.抛掷爆破在露天台阶式采矿中应用的探讨[J].化工矿物与加工,1992(6):1-4.PAN Jing-lan.Application of casting blast instepped-faced mining in surface mine[J].IndustrialMinerals and Processing,1992(6):1-4.
    [4]李祥龙.高台阶抛掷爆破技术与效果预测模型研究[D].北京:中国矿业大学力学与建筑工程学院,2010.
    [5]周伟,才庆祥,李克民.露天煤矿抛掷爆破有效抛掷率预测模型[J].采矿与安全工程学报,2011,28(4):614-617.ZHOU Wei,CAI Qing-xiang,LI Ke-min.Predictionmode of effective stripping ratio of casting blast inopen pit[J].Journal of Mining&Safety Engineer-ing,2011,28(4):614-617.
    [6]杨国华,张殿辉.浅谈影响露天矿抛掷爆破效果的因素[J].内蒙古煤炭经济,2008(6):55-57.YANG Guo-hua,ZHANG Dian-hui.The analysis ofeffective factors of pit-open cast blasting[J].InnerMongolia Coal Econom,2008(6):55-57.
    [7]李祥龙,刘殿书,何丽华,等.露天煤矿的台阶高度对抛掷率的影响[J].爆炸与冲击,2012,32(2):211-215.LI Xiang-long,LIU Dian-shu,HE Li-hua,et al.In-fluences of bench height of an open-pit coal mine oncast percentage[J].Explosion and Shock Waves,2012,32(2):211-215.
    [8]李祥龙.孔距、排距对高台阶抛掷爆破抛掷率的影响[J].北京理工大学学报,2011,31(11):1265-1269.LI Xiang-long.Effect of casting parameters on thecast percentage of high bench cast blasting[J].Transactions of Beijing Institute of Technology,2011,31(11):1265-1269.
    [9]马力,李克民,丁小华,等.黑岱沟露天矿抛掷爆破效果的模糊综合评价[J].金属矿山,2011(9):58-60.MA Li,LI Ke-min,DING Xiao-hua,et al.Fuzzysynthetic evaluation on casting blast effect of Heidai-gou surface coal mine[J].Metal Mine,2011(9):58-60.
    [10]徐全军,张庆明,恽寿榕.爆破地震峰值的神经网络预报模型[J].北京理工大学学报,1998,18(4):472-475.XU Quan-jun,ZHANG Qing-ming,YUN Shou-rong.Neural network model for forecasting peak ac-celeration of blasting vibration[J].Journal of Bei-jing Institute of Technology,1998,18(4):472-475.
    [11]张艺峰,姚道平,谢志招.基于BP神经网络的爆破振动峰值及主频预测[J].工程地球物理学报,2008,5(2):222-226.ZHANG Yi-feng,YAO Dao-ping,XIE Zhi-zhao.The predition of blasting vibration peak value&main frequency by BP neural network[J].ChineseJournal of Engineering Geophysics,2008,5(2):222-226.
    [12]李祥龙,何丽华,栾龙发,等.露天煤矿高台阶抛掷爆破爆堆形态模拟[J].煤炭学报,2011,36(9):1457-1462.LI Xiang-long,HE Li-hua,LUAN Long-fa,et al.Simulation model for muckpile shape of high benchcast blasting in surface coal mine[J].Journal ofChina Coal Society,2011,36(9):1457-1462.
    [13]姚金阶,朱以文.岩体爆破参数设计的神经网络模型[J].爆破,2005,22(2):34-36.YAO Jin-jie,ZHU Yi-wen.The neural networkmodel of rock blasting parameters design[J].Blas-ting,2005,22(2):34-36.
    [14]韩亮.黑岱沟露天煤矿高台阶抛掷爆破爆堆形态的研究[D].北京:中国矿业大学力学与建筑工程学院,2010.
    [15]郭连军,王智静,牛成俊.爆破优化的神经网络模型[J].工程爆破,1996,2(2):11-15.GUO Lian-jun,WANG Zhi-jing,NIU Cheng-jun.The neural network model for blasting optimization[J].Engineering Blasting,1996,2(2):11-15.
    [16]张成良,杨阳,梁开水,等.岩壁梁爆破参数优化的神经网络模型[J].工程爆破,2006,12(1):22-25.ZHANG Cheng-liang,YANG Yang,LIANG Kai-shui,et al.Neural network model of blasting pa-rameters optimization of crane beam at rockwall[J].Engineering Blasting,2006,12(1):22-25.
    [17]刘希亮.基于GA-BP神经网络抛掷爆破效果预测与分析[D].北京:中国矿业大学地球科学与测绘工程学院,2011.
    [18]GALAVIZ P,MELIN P,TRUJILLO L.Improve-ment of the back propagation algorithm using(1+1)evolutionary strategies[J].Studies in Computa-tional Intelligence,2010,312:287-302.
    [19]DOMBI G W,NANDI P,SAXE J M,et al.Predi-cation of rib fracture injury outcome by an artificialneural network[J].The Journal of Trauma,1995,39(5):915-921.

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