CAJ | 학술논문

为改善新疆某铅锌矿采用无底柱分段崩落法开采的爆破效果及降低爆破开采成本，本文从该矿区特殊的地质条件和现有的开采技术水平出发，利用人工神经网络建立爆破过程中采矿成本的预测与控制模型，对单位炸药消耗量、扇形深孔排距、孔底距、崩矿步距等爆破参数进行优化试验。试验与模型预测结果表明：炸药单耗为0．85kg/m3、排距为1．75m、孔底距为2．1m、崩矿步距为5．25m时能够取得最佳效益；利用BP神经网络对采矿成本的预测与控制模型的方法，可准确地对爆破参数进行优化，为爆破开采参数优化设计提供新思路。
위개선신강모연자광채용무저주분단붕락법개채적폭파효과급강저폭파개채성본，본문종해광구특수적지질조건화현유적개채기술수평출발，이용인공신경망락건립폭파과정중채광성본적예측여공제모형，대단위작약소모량、선형심공배거、공저거、붕광보거등폭파삼수진행우화시험。시험여모형예측결과표명：작약단모위0．85kg/m3、배거위1．75m、공저거위2．1m、붕광보거위5．25m시능구취득최가효익；이용BP신경망락대채광성본적예측여공제모형적방법，가준학지대폭파삼수진행우화，위폭파개채삼수우화설계제공신사로。
In order to improve the blasting effect and decrease the payment with non-pillar sublevel caving mining method for lead-zinc deposit in Xinjiang .According to the special geological of mining area and the existing mining technology ,an artificial neural network model for forecasting and controlling the mining cost was established to search for the best blasting parameters in the process of blasting .The experiment with the model predictions turned out that when explosives consumption was 0 .85kg/m3 ,the row spacing was 1 .75m ,the bottom of the hole distance was 2 .1m ,caving step distance was 5 .25m certain had the best performance .All in all ,the BP neural network model can accurately optimize the blasting parameters ,and provide a new idea for optimal design of mining blasting parameters .