欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为了弥补金川矿山棒磨砂充填料供应不足以及对选矿全尾砂与粉煤灰废弃物的资源化,针对金川镍矿下向分层进路充填法采矿安全生产要求,开展了全尾砂和棒磨砂混合充填料合理配比的试验研究首先进行了全尾砂与棒磨砂配比、水泥添加量、粉煤灰掺入量以及料浆浓度的多因素正交试验;然后建立神经网络模型进行试验样本的学习训练,由此建立充填体强度和沉降损失率与影响因素的隐含关系在此基础上,进行不同料浆配比的充填体强度与沉降损失率的预测,从而实现了对有限试验样本的知识外延并通过对扩大样本的回归分析,揭示了影响充填体强度和沉降损失率的因素与变化规律;确定了满足金川镍矿安全充填法采矿的全尾砂和棒磨砂混合充填料的合理配比参数,为全尾砂的工业化应用奠定了基础。
英文摘要：
In order to make up the filling shortage of rod milling sand and make full use of concentrator tailings and the fly ash of Jinchuan mine,the experiment of optimal ratio of whole tailings and rod milling sand was carried out according to the safety production requirement of downward sublevel drift filling.The orthogonal tests of whole tailings and rod milling sand ratio,cement addition amount, fly ash incorporation and slurry concentration were carried out first.Then,the neural network model was established for the learning and training of samples,and the implied relationship between the strength of filling body and compression coefficient and the influence factors was founded.On the basis of this relationship,the prediction of the strength of filling body and compression coefficient of different ratio were done to realize the knowledge denotation of limited samples.The influence factors and variation law of filling body strength and compression coefficient were revealed by the regression analysis of expanded samples.The reasonable ratio of whole tailings and rod milling sand of Jinchuan nickel mine was determined.These results lay a foundation for the whole tailings industrial application.
同期刊论文项目
同项目期刊论文
期刊信息
位置：