东鞍山铁矿浮选动力学研究

本文从理论上阐明了物料整体的浮选行为遵从一固定速率常数K的n级速率方程,并从微观角度分析物料K值遵从Г分布。结合东鞍山矿石分批浮选试验结果,优化出不同浮选条件下的动力学参数,进而找出它们与操作变量之间的数学关系。     

煤泥浮选动力学模型的研究

通过分批浮选试验和大量的小浮沉试验，研究了不同密度级煤泥浮选动力学模型，以及浮选剂添加量对煤泥浮选速率的影响关系，得出了煤泥浮选速率常数与煤泥密度和捕收剂用量及起泡剂用量之间的数学模型。并利用了不同密度级的浮选速率常数对实际浮选生产结果进行了预测。     

黑钨矿、白钨矿及萤石异步浮选动力学研究

以苯甲羟肟酸为捕收剂,采用分批浮选试验方法,研究了柿竹园黑钨矿、白钨矿及萤石可浮性随浮选时间的变化关系,并根据浮选动力学基本原理,对白钨矿、黑钨矿及萤石的浮选动力学特性进行了分析。结果表明,浮选速度常数K值在浮选过程中是不断变化的,调整剂柠檬酸可显著扩大矿物浮游速度之间的差异,在原有经典动力学模型的基础上,通过适当改进导出了分速浮选动力学方程的一般形式,分速模型对浮选数据的拟合精度优于经典动力学模型。研究认为,异步浮选技术能实现矿物的个性化、差异性浮选,充分体现了"和谐的精细工艺技术"的重要特征。     

铵-胺盐强化硫化体系中硅孔雀石浮选动力学研究

浮选过程是一个相当复杂的物理化学过程,受到诸多内外因素的影响,而浮选动力学正是研究在各种影响因素下浮选过程随时间的变化规律。本研究对碳酸氢铵、乙二胺磷酸盐、碳酸氢铵与乙二胺磷酸盐组合铵(胺)盐对硅孔雀石的强化硫化作用进行浮选动力学研究。首先在不同条件下对硅孔雀石进行分批刮泡浮选试验,然后分别计算了在不同条件下硅孔雀石的浮选速率并进行浮选动力学拟合,构建了不同浮选体系下硅孔雀石的浮选动力学模型。研究表明硅孔雀石在碳酸氢铵与乙二胺磷酸盐组合铵(胺)盐的体系中的浮选速率常数比在单一的碳酸氢铵、乙二胺磷酸盐体系中要高,从而引起硅孔雀石回收率的增加。     

捕收剂AY作用下不同粒级石英浮选动力学模型研究

通过单矿物浮选试验, 研究了pH=4.0时、阳离子捕收剂AY作用下不同粒级石英上浮率随浮选时间的变化规律, 并采用6种浮选动力学模型进行了拟合。结果表明, 石英粒度越细, 极限上浮率和浮选速率常数越小; 增大捕收剂AY浓度, 石英极限上浮率和浮选速率常数提高, 这与捕收剂吸附密度和颗粒与气泡碰撞、粘附概率有关。该石英的浮选过程符合一级动力学模型, 其拟合优度R²可达0.98以上。     

目标矿物与全浮成分兼用分速浮选模型

本文对目标矿物与全部浮出成分的浮选动力学过程进行了研究。工业矿石可用离散的形式,以速率常数K值大小进行分组,由此建立起分速浮选模型。该模型不仅可用来描写目标矿物的浮选特性,也能较好地模拟全部浮出成分的动力学行为。经实践检验:该模型预报值与试验实测值十分拟合。     

蓝晶石、石英及黑云母的浮选动力学研究

以十二胺为捕收剂,淀粉为抑制剂,采用单矿物分批浮选的方法,研究了蓝晶石、石英及黑云母在自然pH条件下的可浮性随浮选时间的变化关系,并对三种矿物的浮选动力学特性进行了分析。结果表明,浮选速度常数在浮选过程中不是恒定不变的,抑制剂淀粉的加入可显著扩大矿物之间浮游速度的差异,采用经典一级动力学模型对浮选过程进行了模拟,拟合后的石英、黑云母及蓝晶石模型回收率拟合值与试验值相关性R2分别为0.97、0.98和0.96,表明模型拟合精度较高可模拟矿物的浮选过程。     

浮选经验模型及操作变量的最佳选择

文章利用作者过去建立的浮选模型,结合试验室正交试验结果,求出模型中的有关浮选特征的常数,再用浮选过程中的操作变量用逐步回归的方法包括到模型中去。最后利用浮选模拟器对小型试验结果推广到连续浮选时的操作条件进行寻优。在进行求解速度常数值的非线性回归及进行操作变量寻优时,分别使用了Powell 及Simplex直接寻优方法。     

不同粒度煤泥浮选特性的试验研究

进行了粒度上限为1mm煤泥的浮选特性研究,通过窄粒级煤泥浮选动力学试验,考察了叶轮转速与充气量对浮选动力学常数和浮选精煤产率的影响规律。结果表明,对于不同粒度级煤,叶轮转速变化比充气量变化对浮选速率的影响更为显著。在充气量较低时,叶轮转速对浮选速率常数的影响较明显,浮选速率常数随叶轮转速的提高而增大。对于同一粒度级的煤,当充气量保持不变时,浮选精煤产率和浮选速率常数随叶轮转速的提高而增加。     

大尺寸浮选槽的特征

通过与选矿厂实际操作条件进行比较,对大尺寸浮选槽的设计和操作条件进行了评价.研究的主要目的在于确定以经验规则为基础的按比例放大的时间放大因数.试验在Minera Escondida公司的粗选回路中进行.粗选回路主要由6个平行的、每排由9个160 m3的自吸式浮选槽组成.通过直接取样和一排粗选中每个浮选槽的数质量平衡来估计粗选回路的动力学参数,并对整个过程的数质量平衡进行了调整.用这些信息来拟合不同的浮选动力学模型.研究结果表明,矩形分布函数最适于描述工业操作过程的分布速率常数.然后建立一个粗选模拟器,用来描述不同操作参数(精矿产率、固体含量和给矿品位)和进入每个浮选槽的矿浆体积流量的变化.在本研究中,从粗选回路中对给矿平行地进行取样,并同时进行实验室浮选试验.对分批浮选试验建立动力学模型,以确定由分批试验到工业浮选的按比例放大的时间因数.结果表明,160 m3大尺寸浮选槽的按比例放大时间因数与以前测定的规格较小但回收率相近的自吸式浮选槽的结果很相近.并且,用参数ψ对分批试验和工业生产中的一排浮选机的混合作用的影响进行了量化,该参数可区分动力学变化和混合作用变化对按比例放大时间因数的影响.此时,粗选工艺过程一般能够达到预期的冶金目标,并且最佳的分离效果也可以获得.这种诊断系统能够获得相关的工艺过程内部状态的信息,因此可用来更好地设计、操作和控制浮选回路.     

Estimation of flotation kinetic parameters by considering interactions of the operating variables

In this study, the classical first-order kinetic model was combined with a properly built statistical model based on a factorial experimental design, in order to accurately predict the rougher flotation efficiency for various flotation conditions. A three-level, three-factor experimental design was used to develop a statistical model to predict each of the kinetic model parameters as a function of the air flow rate, the feed grade and the froth thickness (or the pulp level). The statistical evaluation of the experimental results indicated that the ultimate recovery, the rate constant and time correction factor are not constant but each of these kinetic model parameters can be defined as a function of the variables considered. Furthermore, the rate of change in the kinetic parameters due to the feed grade fluctuation and their effects on the metallurgical performance can accurately be predicted by using the models developed. Thus, in order to reduce the detrimental effect of the feed grade fluctuations on the metallurgical performance, the operating variables of the flotation can be manipulated to obtain the desired concentrate grade. In addition, predictions with an error of less than 3.3% indicated that the versatility and viability of the classical first-order kinetic model could be improved by using the models developed.     

Characterization of large size flotation cells

Design and operating conditions of large size mechanical flotation cells were evaluated by comparing it with the actual operating conditions in a plant. The objective was to determine the time scale-up factor, typically based on empirical rules. Experiments were conducted on the rougher flotation circuit at Minera Escondida Ltd. The circuit consisted of self-aerated mechanical cells of 160 m³, arranged in six parallel banks with nine cells each.The rougher circuit flotation kinetics was evaluated from direct sampling and local mass balances around each cell of the bank. Adjusted overall mass balances were also developed. This information was used to fit different kinetic flotation models, and it was found that the rectangular distribution function was the most appropriate to describe the distributed rate constant for industrial operation. Then, a rougher flotation simulator was developed to describe the actual operation in terms of the operating variables (mass flow rate, solid percentage, feed grade) and the actual volumetric flow rate entering to each cell. In this study feed pulp samples were taken in parallel from the rougher circuit and were simultaneously floated in laboratory. The kinetic behavior was then modeled at a laboratory batch scale in order to determine the time scale-up factor between laboratory batch flotation data and industrial size flotation. The time scale-up factor observed for large sized cells, 160 m³, was found reasonably similar to those previously determined for self-aerated mechanical cells, but of lower size, operating at similar recoveries. In addition, the relative effect of mixing, between laboratory batch and an industrial flotation bank was quantified by the ϕ parameter, separating the impact that kinetic and mixing changes have on the time scale-up factor.In general, the rougher flotation operation was found to reach the predicted metallurgical target, and that the optimal separability criterion was also respected.The diagnostic generates information about the internal state of the process and helps to identify potential improvements for design, operation and control of the circuit.     

A computational fluid dynamics model for the flotation rate constant,Part I: Model development

A Computational Fluid Dynamics (CFD) model for the prediction of the flotation rate constant in a standard Rushton turbine flotation tank was developed. The premise for the model development was the assumption that separation by flotation is a first order rate kinetic process. An Eulerian–Eulerian framework in conjunction with the dispersed k–ε turbulence model was supplemented with user defined functions to implement the local values of the turbulent flow into a kinetic model. Simulations were performed for quartz at different operational conditions. The numerical predictions were validated against experimental data and analytical computations using the fundamental flotation model of Pyke et al. (2003). The results showed that the CFD-based model not only captured the trend of experiments for a range of particle sizes but also that the CFD yielded improvements in the predictions of flotation rate constant compared with the theoretical calculations. It was found that the CFD model is able to predict the flotation rate constants of the quartz particles floating under different ranges of hydrophobicity, agitation speed and gas flow rates with lower root mean square deviation compared with the theoretical computations.     

An exponential decay relationship between micro-flotation rate and back-calculated induction time for potential flow and mobile bubble surface

Flotation researchers have long hypothesised that particles have inherently different flotation rates under the same operating conditions because they have different induction times in the flotation cell. The relationship between flotation rate constant and induction time, however, has yet to be explored. Here we analysed the relationship between micro-flotation rate and back-calculated induction time for galena and sphalerite particles. The floatability of the particles was controlled by depression with potassium chromate (galena) and activation with copper sulphate (sphalerite). The bubble rise velocity vs. size in the micro-flotation experiments was determined by high speed video microscopy and followed the prediction for bubbles with the fully mobile air–water interface. Therefore, the theoretical analysis of the micro-flotation results was carried out, based on the potential flow model for water flow around a mobile bubble surface. The relationship between micro-flotation rate constant and back-calculated induction time was found to rapidly decay exponentially. In this model, flotation rate constant is highly sensitive to induction time. For example, a doubling or tripling of induction time results in an order-of-magnitude decrease in flotation rate constant.     

基于LM-BP神经网络的浮选药剂流量预测模型研究

结合东鞍山选矿厂浮选流程的实际工况,采集现场浮选流程的关键过程变量、工艺指标,提出了基于LM-BP神经网络的浮选药剂流量预测模型。数据交叉验证的结果表明,该方法能够在保证精矿品位、回收率等指标满足生产要求的前提下,合理预测浮选药剂制度,使浮选矿浆达到最佳矿化状态,进而优化浮选各项指标,对于降低选厂浮选流程的生产成本有一定的参考价值。     

Collection zone kinetic model for industrial flotation columns

The collection zone recovery of a flotation column was modeled using a rectangular distribution function for the kinetic rate constant and a tank in series model with different vessel sizes for the residence time distribution. It was demonstrated that an analytical expression can be obtained and that data from large industrial columns fits well, keeping the parsimony principle by using a simple and practical solution. An example for the estimation of the maximum kinetic rate constant, useful for scale-up purposes, is shown using data from industrial flotation columns.     

基于混料设计和响应曲面法的云南某铜尾矿选铋工艺参数优化

某铜选厂尾矿试样中铋品位为3.94%,铋主要以自然铋的形式存在,其次为黄铜矿、方铅矿中铋。针对试样性质特点,采用浮选工艺流程回收铜尾矿中的铋。为进一步优化浮选指标,首先以乙硫氮和丁基黄药用量为自变量,铋的回收率为因变量建立混料模型,确定组合捕收剂乙硫氮和丁基黄药的最优配比。在此基础上,利用中心复合设计进行响应曲面设计,以磨矿细度、硫化钠用量、碳酸钠用量、组合捕收剂用量为自变量,铋的回收率为因变量,建立4因素5水平数学模型。然后按模型设计试验进行1次粗选浮选试验,对试验结果进行方差分析,验证模型的可靠性。最后依据响应曲面法确定的最佳浮选条件进行“1粗3精2扫”浮选闭路试验。结果表明：①在磨矿细度为-0.074 mm占85%、氧化钙用量为4 kg/t、硫化钠用量为150 g/t、碳酸钠用量为900 g/t、25号黑药用量为100 g/t、组合捕收剂总用量为200 g/t的条件下,组合捕收剂乙硫氮和丁基黄药的最优配比为4∶1。②方差分析模型的P<0.05,磨矿细度和硫化钠用量对铋的回收率影响显著;响应曲面法确定的最佳粗选条件为磨矿细度-0.074 mm占86%、硫化钠用量140 g/t、碳酸钠用量750 g/t、组合捕收剂用量250 g/t,预测铋的最大回收率为83.77%,实际铋的回收率为83.85%。③根据响应曲面法确定的最佳浮选条件,采用“1粗3精2扫”的闭路浮选试验,获得精矿铋品位24.47%、铋回收率79.25%的铋精矿,铋回收率较原浮选闭路流程提高近2个百分点。研究结果表明混料设计和响应曲面法可用于优化铋浮选的工艺参数,具有较高的可信度。     

应用JKSimFloat进行矿物可浮性的模拟研究

由于浮选过程自身的复杂性以及众多因素对浮选过程的影响,浮选的建模一直比较困难。通常采用浮选一阶动力学模型进行浮选建模,本文根据一阶浮选速率k将矿物划分为不同的可浮性组分,通过最小化误差平方和的方法拟合得到不同可浮性组分的浮选速率,这将有利于对浮选的建模研究。