含碳酸盐萤石矿石全弱酸性浮选新工艺

对含碳酸盐较高的萤石矿石提出了不加纯碱的全弱酸性浮选新工艺,获得CaF_298.21％、SiO_20.67％,回收率为93.25％的良好指标,实现了低模数碳酸盐—萤石矿石的高纯分离。     

基于BP神经网络的加药控制系统研究

浮选是最重要的选矿方法之一,煤矿浮选工艺自动加药控制问题是影响浮选效果的重要因素;传统加药控制主要是由加药工根据生产经验来控制,为了解决浮选精度低这一问题,文中提出采用BP神经网络作为加药控制系统加药量的预测模型,并采用动量项方法对其进行优化,通过仿真得出动量项法网络和测试样误差曲线,说明带动量项改进的神经网络更容易满足网络精度的要求,并且该方法能够有效地降低误差、减小浪费。     

金选别工艺的发展与深化

本文阐述了充分考虑矿石性质,探索出混合浮选的分步流程,恰当的施用多元扑收剂所产出的“协同效应”,稳定和强化选别工艺,收到提高选金技术指标的效果。     

Interpretable modeling of metallurgical responses for an industrial coal column flotation circuit by XGBoost and SHAP-A “conscious-lab” development

Surprisingly, no investigation has been explored relationships between operating variables and metallurgical responses of coal column flotation (CF) circuits based on industrial databases for under operation plants. As a novel approach, this study implemented a conscious-lab “CL” for filling this gap. In this approach, for developing the CL dedicated to an industrial CF circuit, SHapley Additive exPlanations (SHAP) and extreme gradient boosting (XGBoost) were powerful unique machine learning systems for the first time considered. These explainable artificial intelligence models could effectively convert the dataset to a basis that improves human capabilities for better understanding, reasoning, and planning the unit. SHAP could provide precise multivariable correlation assessments between the CF dataset by using the Tabas Parvadeh coal plant (Kerman, Iran), and showed the importance of solid percentage and washing water on the metallurgical responses of the coal CF circuit. XGBoost could predict metallurgical responses (R-square > 0.88) based on operating variables that showed quite higher accuracy than typical modeling methods (Random Forest and support vector regression).     

磷石膏提质降杂实验研究

磷石膏的综合利用对保护环境、促进企业可持续健康发展具有重要意义,但是磷石膏中的磷、氟、二氧化硅等杂质影响其利用。针对云南磷石膏中二氧化硅含量高的问题,采用正浮选工艺开展了磷石膏提质降杂的实验研究。通过单因素条件实验获得了合适的工艺参数：浮选温度为15 ℃、矿浆pH为2、十二胺用量为300 g/t。在此条件下,进行了“一粗二精”的正浮选开路流程实验,获得了二水石膏（CaSO₄·2H₂O）质量分数为97.5%、二氧化硅质量分数为1.17%的精矿,所得精矿达到了GB/T 23456—2018《磷石膏》一级品指标的要求;二水石膏回收率为98.58%、二氧化硅去除率为92.23%。通过正浮选不仅成功实现了二水石膏和二氧化硅的有效分离,而且磷石膏中的水溶磷和水溶氟也得到了有效去除,从而提高了磷石膏的品质。     

某含铜尾矿粗砂工艺矿物学特征及选矿试验研究

为查找铜损失在尾矿中的原因并制定选矿回收工艺,对某低品位含铜尾矿粗砂进行了工艺矿物学分析和选矿试验研究。结果表明：含铜矿物主要是黄铜矿（CuFeS2）,嵌布粒度微细且呈浸染状分布,未能充分单体解离而损失在尾矿中。经过选矿优化试验确定粗尾砂可采用立式搅拌磨,使微细粒级铜矿物充分单体解离;然后,采用优先浮选工艺回收铜,闭路试验可获得Cu品位18.02%、Cu回收率41.05%的铜精矿。     

Progress in flotation de-silica

1　INTRODUCTIONBayer sprocessisatypicalmethodtoproducea luminumoxidefrombauxite .Forthediasporic baux ite ,theBayer sprocesscaneconomicallyproducealu minumoxideonlywhenthemassratioofAl2 O3toSiO2 >10 .However ,inChina ,thealuminumoxidewasmainlyproducedbyusing“sinteringprocess”or“in parallelBayer sinteringcombination process”technologiesbecausethediasporic bauxiteischarac terizedbyhighcontentofaluminumoxideandsilicabutlowAl2 O3/SiO2 (average 5 6 ) .Thesetwotech nologieshavetheproble…     

ADSORPTION MECHANISMS OF HS-IONS ON SULPHIDE MINERAL SURFACES RELATED TO Na_2S-INDUCED FLOTATION

The adsorption mechanisms of HS~- ions existing in air-saturated alkaline solutions on sulphide minerals (including pyrite, arsenopyrite, chalcopyrite and galena) were investigated. The measurement of adsorption density, solvent extraction-chemical analysis of neutral sulphur at the surfaces, measurements of pulp potential and voltammogram, and flotation tests were done. Both the electrochemical and non-electrochemi cal adsorption models of HS~- ions were established. The former was observed and resulted in the formation of neutral sulphur (S°)when the pyrite and arsenopyrite were chosen, and hence renders the surfaces hy drophobic and induced the two minerals flotation. It is called Na_2S-induced flotation. On the other hand, the latter took place and did not produce S° when the chalcopyrite and galena were selected, and hence de presses the collectorless flotation of the two minerals. The adsorptions of HS~- ions were mainly influenced by potentials, pH and the electron structures of the mineral surfaces.     

PRESSURE DISTRIBUTION IN THE AIR-SPARGED HYDROCYCLONE

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Flow field in air-sparged hydrocyclone

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