陈庆凯;赵文龙;郭赵杰;韦学塔;田益林;
CHEN Qing-kai;ZHAO Wen-long;GUO Zhao-jie;WEI Xue-ta;TIAN Yi-lin;School of Resources and Civil Engineering, Northeastern University;Yanshan Open Pit Mine,HBIS Group Co., Ltd.;

• 1:东北大学资源与土木工程学院
• 2:河北钢铁集团研山露天铁矿

摘要(Abstract)：

露天矿爆破效果的好坏直接影响矿山后续生产工序和效益。为此建立一种科学有效的爆破效果评价模型,对爆破效果进行分析,然后根据分析结果指导后期矿山生产。于是基于模糊神经网络理论,选取了大块率、根底、爆破振动、延米爆破量等8个评价指标,采用10分制将爆破效果等级划分为5级,建立了爆破效果综合评价模型。选取研山露天矿实际爆破数据,利用MATLAB软件,对三种不同孔径爆破方案进行评价。评价结果表明:φ250 mm孔径爆破评价结果在Ⅱ级及以上的比例达到74.07%,效果最好;φ310 mm孔径爆破评价结果在Ⅱ级及以上的比例为50.85%,效果最差。结果表明模型分析结果与现场实际情况符合,评价结果可为矿山爆破方案制定与决策提供依据。
The blasting effect of open pit directly affects the subsequent production process and benefit of mine. The aimis to establish a scientific and effective evaluation model of blasting effect and to guide the later mining production by analyzing the blasting effect. Eight evaluation indexes such as boulder ratio, root bottom, blasting vibration and lengthening blasting amount were selected. The blasting effect level was divided into 5 levels by though 10 degrees. Based on the metric system, a comprehensive evaluation model of blasting effect was established based on fuzzy neural network. According to the actual data of blasting in Yanshan open-pit mine, three different aperture blasting schemes were evaluated by MATLAB software. The evaluation results showed that the φ250 mm aperture blasting effect is the best, and the φ310 mm aperture blasting effect is the worst. The evaluation results are consistent with the actual situation on site. The results show that the model analysis results are consistent with the actual situation in the field, the evaluation method is objective and accurate,which can provide a basis for the formulation and decision of mine blasting scheme.

关键词(KeyWords)： 模糊神经网络;露天台阶爆破;爆破效果评价;隶属函数
fuzzy neural network;open bench blasting;evaluation of blasting effect;membership function

Abstract:

Keywords:

基金项目(Foundation):

作者(Authors): 陈庆凯;赵文龙;郭赵杰;韦学塔;田益林;
CHEN Qing-kai;ZHAO Wen-long;GUO Zhao-jie;WEI Xue-ta;TIAN Yi-lin;School of Resources and Civil Engineering, Northeastern University;Yanshan Open Pit Mine,HBIS Group Co., Ltd.;

参考文献(References)：

• [1] 雷振,杨仁树,陶铁军.基于未确知测度理论的台阶爆破效果综合评价[J].煤炭学报,2015,40(2):353-359.LEI Z,YANG R S,TAO T J.Comprehensive evaluation of step blasting effect based on unascertained measure theory[J].Journal of China Coal Society,2015,40(2):353-359.
• [2] 黄刚,周文涛,张建华.东沟钼矿露天台阶爆破参数优化研究[J].金属矿山,2018(8):1-6.HUANG G,ZHOU W T,ZHANG J H.Optimization of blasting parameters of open-pit steps in Donggou Molybdenum Mine[J].Metal Mines,2018(8):1-6.
• [3] 张建华,李泽安.矿山爆破效果的可拓学评价[J].金属矿山,2015(11):33-36.ZHANG J H,LI Z A.Extenics evaluation of mine blasting effect[J].Metal Mines,2015(11):33-36.
• [4] 袁绍国,王振涛,耿荣,等.基于BP神经网络的爆破参数优化研究[J].煤炭技术,2017,36(11):10-11.YUAN S G,WANG Z T,GENG R,et al.Study on optimization of blasting parameters based on BP neural network[J].Coal Technology,2017,36(11):10-11.
• [5] 张永梅,马礼,孙海燕,等.基于模糊神经网络的程序设计能力、实践与创新能力评价方法[J].实验室研究与探索,2017,36(2):18-22.ZHANG Y M,MA L,SUN H Y,et al.Evaluation of programming capabilities,practice and innovation capabilities based on fuzzy neural networks[J].Laboratory Research and Exploration,2017,36(2):18-22.
• [6] 韩红桂,林征来,乔俊飞.基于UKF的增长型模糊神经网络设计[J].控制与决策,2017,32(12):2-2.HAN H G,LIN Z L,QIAO J F.Design of growth fuzzy neural network based on UKF[J].Control and Decision,2017,32(12):2-2.
• [7] 李启月,孔德国,吴正宇,等.基于T-S模型的模糊神经网络在地下硐室超挖预测中的应用[J].矿冶工程,2017,37(1):1-4.LI Q Y,KONG D G,WU Z Y,et al.Application of fuzzy neural network based on T-S Model in overburden prediction of underground chambers[J].Mining and Metallurgical Engineering,2017,37(1):1-4.
• [8] 李清,程阳,于强,等.基于改进层次分析法的爆破效果影响因素[J].工程爆破,2017,23(3):1-4.LI Q,CHENG Y,YU Q,et al.Factors affecting blasting effect based on improved analytic hierarchy process[J].Engineering Blasting,2017,23(3):1-4.