铜密闭鼓风炉生产效益的回归分析

通过铜密闭鼓风炉生产过程中关键指标的回归分析,寻找降低消耗、增加产出、提高经济效益的有效途径     

A kinetic model for the acid-oxygen pressure leaching of Ni–Cu matte

A semi-empirical mathematical model for the acid-oxygen pressure leaching of Ni–Cu matte is presented, based on data from batch leaching experiments. The primary controlling factor in the leaching process is found to be galvanic inhibition of the more highly oxidized copper and nickel sulfide species by less oxidized species, particularly Ni alloy and Ni₃S₂. The leaching rate of many species is greatly reduced by the presence of one or both of these phases, and others will not commence leaching until neither is present. The mathematical model is based on first-order chemical reaction controlled rate expressions, as the reactions occurring are electrochemical in nature. Mass transfer effects are included only empirically. Some possibly diffusion-related phenomena are noted, although the model is not extended to incorporate these effects on a fundamental level. The model is verified and extended by the inclusion of several different factors that were tested experimentally. The effects of variations in O₂ flow rate and partial pressure, initial particle size, reaction pulp density and initial acid concentration were all studied, and included in the model. Variations in O₂ flow rate and partial pressure are found to affect the reaction rates via the dissolved oxygen concentration in the solution phase.     

铜鼓风炉节约焦炭的实践

焦碳消耗是铜鼓风炉炼铜中的主要技术指标，本文应用生产中的大量效据。通过正交试验，指出了铜鼓风炉节约焦碳的主要途径，找出了铜鼓风炉节约焦碳的最佳工艺条件。     

Extraction of valuable metals from low nickel matte by calcified roasting−acid leaching process

A calcified roasting−acid leaching process was developed as a highly effective method for the extraction of valuable metals from low nickel matte in the presence of CaO additive. The influences of process parameters on the metal extraction were studied, including the roasting temperature, roasting time, addition of CaO, H₂SO₄ concentration and liquid−solid ratio. Under the optimum condition, 94.2% of Ni, 98.1% of Cu, 92.2% of Co and 89.3% of Fe were recovered. Additionally, 99.6% of Fe was removed from the leachate as goethite by a subsequent goethite iron precipitation process. The behavior and mechanism of CaO additive in the roasting process was clarified. The role of CaO is to prevent the formation of nonferrous metal ferrite phases by a preferential reaction with Fe₂O₃ during the roasting process. The metal oxides (CuO and Ni_xCu_1−xO) remained stable during high-temperature roasting and were subsequently efficiently leached using a sulfuric acid solution.     

高冰镍浸出渣还原浸出工艺研究

以湿法冶炼高冰镍过程中产生的高冰镍浸出渣为研究对象,采用二氧化硫对高冰镍渣加压还原浸出,考察了初始硫酸浓度、液固比、通气方式、浸出温度和浸出时间对高冰镍渣还原浸出过程铜、铁行为的影响;对还原浸出液采用置换沉淀和冷冻结晶的方法,对还原浸出中铜和铁进行分离回收。结果表明：在初始硫酸浓度100 g/L、液固比6 mL/g、反应时间3 h、反应温度90℃、二氧化硫分压0.15 MPa的条件下,铁和铜的浸出率分别为99.35%、77.46%,浸出液中铁几乎全部为亚铁离子;在硫酸含量20～30 g/L、温度70℃、铁粉加入量5.7 g/L、反应时间40 min的条件下,对还原浸出液进行置换沉铜,沉铜率达到了99.70%,渣含铜为67.91%。在温度—10℃、保温时间20～30 min、初始硫酸浓度100 g/L的条件下,对沉铜后液进行冷冻结晶制备硫酸亚铁,铁沉淀率达到了72.6%,七水硫酸亚铁纯度达到了92.93%。     

基于数据挖掘的铜转炉渣产出量预报

为实现铜转炉渣产出量的及时准确预报,提出应用数据挖掘技术从现场积累的大量生产数据中发掘相关规律.首先应用线性回归技术建立了仅考虑主要影响因素(铜锍含铁量)的粗略预报模型,而后,应用神经网络技术建立了考虑到多个次要影响因素的误差补偿模型,从而改进预报效果.利用实际生产数据对模型进行了仿真测试,仿真结果表明,模型预报效果良好.     

Intelligent prediction model of matte grade in copper flash smelting process

Due to the importance of detecting the matte grade in the copper flash smelting process, the mechanism model was established according to the multi-phase and multi-component mathematic model. Meanwhile this procedure was a complicated production process with characteristics of large time delay, nonlinearity and so on. A fuzzy neural network model was set up through a great deal of production data. Besides a novel constrained gradient descent algorithm used to update the parameters was put forward to improve the parameters learning efficiency. Ultimately the self-adaptive combination technology was adopted to paralleled integrate two models in order to obtain the prediction model of the matte grade. Industrial data validation shows that the intelligently integrated model is more precise than a single model. It can not only predict the matte grade exactly but also provide optimal control of the copper flash smelting process with potent guidance.     

铜绿山Ⅵ矿体古代冰钢渣的熔炼过程

本文根据地质文献和考古发掘资料以及冰铜冶炼机理,特别是其含氧化亚铁量比其它遗址的炉渣高１０％的事实,认定铜绿山ⅩⅠ矿体古代炉渣所冶炼的品位为６５％的冰铜是该矿体上层氧化带下部的含黄铁矿较高的铜硫矿石直接入炉的熔炼产物,所使用的冶炼方法属于“硫化矿－冰铜－铜”原则工艺．     

加压酸浸法从烟化炉冰铜中浸出铜和镍的试验研究

烟化炉冰铜主要是采用烟化炉处理低品位铜、锡、镍、锌等物料时产生的中间产物,主要含铜、镍、铁、硫等元素,从中浸出铜和镍具有重要价值。采用加压酸浸法从烟化炉冰铜中浸出铜和镍,试验研究了时间、温度、氧分压、液固比、粒度等因素对铜、镍、铁浸出率的影响。试验结果表明：烟化炉冰铜粒度球磨至小于75μm、温度433K、时间3h、氧分压为0.6MPa、液固比4/1mL/g、木质素磺酸钠用量为2‰的优化条件下,铜、镍、铁浸出率分别平均为98.18%、98.42%和26.46%。     

Flow and Heat Transfer Performance of Slag and Matte in the Settler of a Copper Flash Smelting Furnace

Simulation of two‐phase flow in a copper flash smelting settler with simultaneous tapping of slag and matte is carried out using Eulerian‐Eulerian two‐fluid model and the flow and heat transfer performance of slag and matte is examined. Detailed velocity vectors, temperature and volume fraction distributions are obtained. The results show that the small copper droplets will be suspended in the slag. When the droplet diameter is large enough, the slag and matte layer are clearly formed and the dispersion layer between the slag and matte layers becomes thinner at larger droplet sizes and its thickness remains nearly unchanged when the copper droplet diameter is larger than about 500 μm.