Comparison of open and closed circuit HPGR application on dry grinding circuit performance

A conventional cement grinding circuit is composed of a two compartment tube mill, a mill filter which collects the fine material inside the mill and a dynamic air separator where final product with required fineness is collected. In general the material fed to the circuit has a top size of 50 mm which is very coarse for the ball mill. For this purpose, later in 1980s, high pressure grinding rolls (HPGR) has found applications as a pregrinder which increased throughput of the grinding circuit at the same fineness.In early applications, HPGR was operated in open circuit. But later as the operating principle of the equipment based on the compression, some portion of the HPGR discharge recycled back to improve efficiency of the mill or operated closed circuit with classifiers. Within this study effect of open and closed circuit HPGR applications on dry grinding circuit performance was examined. For this purpose sampling studies around three different cement grinding circuit were completed. In the first study, a circuit including open circuit HPGR, ball mill and air separator was sampled and chosen as the basic condition. As the final product size distribution is important for grinding circuit, model structure of each equipment was developed. The second and third surveys were carried out around closed circuit HPGR operation with V and VSK separator to develop models for the separators. Finally the separator models were used in basic condition to simulate closed circuit HPGR application.It was understood from the studies that closed circuit HPGR operation improved the overall circuit efficiency at the same final product fineness by reducing the specific energy consumption.     

Modeling the contribution of specific grinding pressure for the calculation of HPGR product size distribution

Vale, one of the largest mining companies in the world, has prioritized the development of HPGR technology for practical application in its current projects. An existing model for the HPGR, capable of predicting product size distributions, has been evaluated under distinct grinding conditions for one feed material. The effect of grinding pressure and feed size distribution were investigated. The model response showed a clear dependency of product size distribution with specific grinding pressure. As a result, specific grinding pressure was incorporated into the model, allowing for predicting product size distribution at practical values of this important process parameter. Based on this result, a characterization procedure was envisaged so as to produce parameters for the model. The procedure does not require complex experimental procedures, and all of the testing can be carried out in an expedited form in an instrumented bench-scale HPGR, using small samples of about 10 kg. The only analyses required are size distributions. The model was implemented in the Modsim? plant-wide simulator, with facilities to predict product size distribution for any roll diameter, length and speed of an HPGR machine.     

高压辊磨机选型试验的研究现状

结合高压辊磨机中物料粉碎机理,介绍了影响高压辊磨机粉碎效果的关键因素,评述了高压辊磨机设备选型试验的研究现状。高压辊磨机粉碎物料的效果主要受物料性质、辊压机工作参数及粉碎工艺等的影响。通过小型及半工业型高压辊磨机粉碎试验能够为高压辊磨机的设备选型和流程设计提供依据,但试验过程相对复杂。颗粒床活塞压载试验和数学建模尽管能够对矿石料层粉碎的工作压力、比能耗、产品粒度分布等进行有效预测,但和高压辊磨机设备选型的经验公式一样均需要对其适用性进行验证。指出高压辊磨机未来的研究方向为粉碎过程中能量传递模型、矿石碎磨特性及对分选工艺影响等的理论基础研究,以及高压辊磨机在选矿流程中的数值模拟研究。     

基于生产数据的高压辊磨机粉碎建模与模拟

根据工业流程考查数据对凹山选厂超细碎工段的高压辊磨机粉碎进行了数学建模。利用所建粉碎模型以及以分配曲线形式表示的分级模型对高压辊磨机与3 mm筛分作业构成的闭路粉碎流程进行了模拟计算。计算结果证明了这种高压辊磨机模型及建模方法的有效性和实用性。     

A novel approach for the modelling of high-pressure grinding rolls

The HPGR technology has become more attractive to the copper industry because of its high throughput capacities and its low specific energy consumptions. A HPGR model, able to give enough information based on pilot plant testing, in order to back up HPGR engineering studies, was developed. The model was based on the physical phenomena of the grinding operation. The model parameters were fitted with pilot scale test results, corresponding to a Chilean copper ore, classified in two lithologies (andesitic and porphyrytic ores). Some sets of data were not used in the fitting stage, to test the predictive capability of the model. The pilot scale tests were performed at the facilities of two HPGR manufacturers, changing operating pressure and rolls peripheral velocity (only one of the manufacturers). The simulated specific energy consumptions and particle size distributions, compared with the experimental data, were considered good enough. The model was able to predict adequately throughput capacity, specific energy consumption and particle size distributions of the edge, centre and total products.     

高压辊磨机粉碎工艺国外应用进展与发展趋势

基于层压粉碎原理,高压辊磨机具有处理量大、能量利用率高、粉碎产品粒度细等特性,已经广泛应用 于冶金矿山领域,且节能降耗效果显著。 文章总结了开路粉碎、边料返回半闭路粉碎和筛分(包括干法筛分和湿法筛 分)全闭路粉碎三种粉碎工艺的选择依据。 结合高压辊磨机在金刚石解离、铁矿球团原料预处理、(半)自磨顽石破碎 和金属矿磨前粉碎领域的典型应用案例,重点阐述了高压辊磨机的粉碎工艺流程、设备型号、操作参数及应用效果。 不断提高粉碎效率、降低粉碎成本仍是高压辊磨机粉碎工艺的发展方向。 虽然多台高压辊磨机串联配置、高压辊磨 机与风力分级设备配置、高压辊磨机与搅拌磨机直接配置等新工艺发展不够成熟,但节能降耗优势明显,有望为冶金 矿山物料高效粉碎提供新的解决方案。     

高压辊磨机工作比能耗的计算预测

高压辊磨机(HPGR)作为一种新型节能设备,在矿石破碎领域应用越来越广泛。根据工艺参数要求,对高压辊磨正确选型是其推广应用的前提。比能耗是HPGR的一项主要运行参数,也是HPGR选型的主要依据之一。提出了一种根据流程工艺参数和矿石抗压强度性质计算评估HPGR比能耗的数学模型,称之为DUCS模型,并应用HPGR工业运行数据对此模型进行了验证。结果表明,此模型能够较好地预测HPGR工作比能耗,是一种试验工作量小、预测精度较高和所需时间短的选型方法。     

Genetic algorithms for the optimisation of the Schwartz–Smith two-factor model: a case study on a copper deposit

Mining companies typically seek ways to hedge risks affecting their production. One useful instrument to mitigate the financial risk is the futures contracts on commodity prices. Information from the transactions in futures markets is publicly available and can be analysed with the Schwartz–Smith two-factor model (SSTF). However, finding the parameters governing this model can be very challenging. This step is done using a deterministic optimisation approach called the Expectation–Maximisation algorithm (EM). The starting values of the model will have a significant effect on the convergence of the EM. To ensure the solution does not get stuck in a local maximum, the EM algorithm is performed multiple times with different starting values. This paper assesses the value of genetic algorithms (GA) to optimise the parameters of the SWTF model. Although they are slower than EM algorithms because they use random number generators to search for the optimal solution, GA optimise a population of solutions instead of working on only one solution at the time. Moreover, a constraint on the range parameter can be applied to ensure the parameter has a sound economic meaning. Once the SWTF parameters have been calibrated on the observation of futures contracts, the model can be used for the simulation of spot and futures prices. To demonstrate the performance of the proposed approach, a case study was conducted on a copper deposit. The simulations based on the SWTF model whose parameters are determined by GA are used. An active management strategy of the stockpile, dependent on discrepancies in commodity futures prices is tested. Results show that the active management strategy produces positive returns over the passive investment approach.     

高压辊磨机粉碎数学建模和计算机模拟研究进展

介绍高压辊磨机粉碎数学模型的研究进展,以及应用粉碎数学模型通过计算机模拟计算进行工业型高压辊磨机粉碎效果预测、粉碎回路流程设计和工艺条件优化的研究进展。     

Predicting the specific energy required for size reduction of relatively coarse feeds in conventional crushers and high pressure grinding rolls

In a previous paper (Morrell, 2009. Predicting the overall specific energy requirement of crushing, high pressure grinding roll and tumbling mill circuits. Minerals Engineering 22 (6), 544–549), an approach was described to predict the specific energy of a range of tumbling mill and crushing/high pressure grinding rolls (HPGR) circuits. In the case of crushing and HPGR circuits, recently acquired data have enabled this approach to be extended to coarser particle size reduction situations. This is achieved through the use of a size-dependent hardness parameter. Crushing and HPGR conditions are described where the use of this parameter should improve the accuracy of specific energy predictions. A worked example is also given.     

基于UVE变量筛选偏最小二乘的LIBS磷精矿浆定量分析

利用激光诱导击穿光谱(Laser Induced Breakdown Spectroscopy, LIBS)技术采集得到磷精矿浆的光谱,基于无信息变量消除(Uniformative Variables Elimination, UVE)方法筛选出与磷元素相关的波长变量,将选择后的波长作为自变量建立偏最小二乘(Partial Least Squares, PLS)回归模型,并与传统全谱PLS和GA-PLS(Genetic Algorithm-Partial Least Squares, GA-PLS)定标模型进行比较。相比全谱PLS,UVE-PLS定标模型的性能更优,其预测均方根误差(Root-mean-square Error of Prediction, RMSEP)由0.38%下降到0.26%,决定系数(R²)从0.59提高到0.72。相比GA-PLS定标模型,UVE方法可以克服GA(Genetic Algorithm, GA)在参量选择上存在随机性的弊端,筛选出的变量仅为全谱的8.76%,而且计算速度更快,分析精度也优于GA-PLS模型。     

煤矿智能化十大\

为充分挖掘瓦斯浓度监测数据的变化规律,实现工作面瓦斯浓度的准确预测,提出了一种基于CS-LSTM的工作面瓦斯浓度智能预测模型。采用样条插值法对瓦斯浓度监测数据的缺失值进行插补,再进行无量纲化处理,得到训练样本;利用布谷鸟搜索(CS)算法对长短期记忆网络(LSTM)的隐藏层层数及其神经元个数、全连接层层数及其神经元个数等4个超参数进行寻优,建立最优瓦斯浓度预测模型,并预测工作面未来12 h的瓦斯浓度。研究结果表明：与LSTM及基于遗传算法(GA)的LSTM模型预测结果相比,在相同迭代次数下,CS算法具有更好的全局寻优能力,有效避免了GA算法易陷入局部最优的不足;基于CS-LSTM预测模型的均方根误差(RMSE)为0.023,该模型与其他2种模型相比精度较高,预测效果较好。

     

Sample requirements for HPGR testing procedure

Green field projects demand relatively large amounts of sample from drill-cores. Besides chemical analysis, samples are required for mineralogy and liberation characterization, physical characterization, concentration tests and a number of tests for crushing and grinding parameters. If the project’s process route includes a possible HPGR grinding stage, lab-scale tests for scale-up and variability analysis are required. HPGR grinding characterization can be carried out in a small diameter roll HPGR, such as the LABWAL. Some commercial labs recommend 20–30 kg samples for steady-state tests, but this is a rather large sample from the point of view of a green field project campaign. The question that is being assessed here is how much sample is really required? Surely, the more material that is available the more reliable will be the test results. However, when the sample mass size is reduced, what is the impact on the data that is produced? In this work, six phlogopitite samples weighing 20 kg were tested in the LABWAL HPGR using six initial hydraulic pressures, 10, 20, 30, 40, 50 and 60 BAR. The specific capacity and specific power factors were determined, as well as the critical angle of nip, and the critical gap. Size distributions were measured and size-mass balance parameters were determined for the Austin model under the range of grinding pressures that were produced. With the data, a hypothetical industrial HPGR for the phlogopitite was designed for a standard capacity of 100 t/h and operating at 2 N/mm² specific grinding force. The work was then repeated using 10 kg samples and 5 kg samples. Results show that, under the conditions that were chosen, samples weighing 5 kg are sufficient for characterization in the LABWAL HPGR.     

参数优化GA-ELM模型在露天煤矿抛掷爆破的预测

为有效指导露天煤矿制定正确生产计划,提高露天煤矿抛掷爆破预测的准确率,在分析露天煤矿抛掷爆破影响因素的基础上,通过"试错法"确定模型最优隐含层节点参数,进而提出一种参数优化后遗传算法(GA)和极限学习机(ELM)相结合的抛掷爆破预测模型。选取网络的输入输出相关参数,针对现有ELM输入权值矩阵和隐含层偏差,采用遗传算法对其进行优化选择;利用某露天煤矿抛掷爆破监测数据对该模型进行实例分析,并将RBF,BP,SVM,GA-BP模型预测结果与该模型进行对比分析;并引入Weibull模型,通过预测控制参数ɑ,β模拟爆堆形态。研究结果表明:(1)通过"试错法"确定GA-ELM模型最优隐含层节点数为39,有效降低系统的仿真误差,该参数下仿真误差值为0.137 7;(2)相较于传统ELM预测模型,通过遗传算法优化后,有效抛掷率,松散系数以及抛掷距离均得出更小的均方误差MSE值(0.258 0,1.748 5×10-4,3.618 4)和更高的决定系数R2值(0.986 4,0.995 3,0.970 6),改进后的GA-ELM具有更好的拟合效果和泛化能力;(3)通过与其他智能算法如BP,RBF,SVM,GA-BP相比,改进后的GA-ELM测试结果(均方误差,决定系数,仿真误差)明显优于其他预测模型,有效提高预测精度;(4)利用训练完成的GA-ELM网络预测爆堆形态时,控制参数a,β的预测误差均未超过5%,预测爆堆曲线接近真实爆堆曲线。     

A preliminary investigation into the feasibility of a novel HPGR-based circuit for hard,weathered ores containing clayish material

The paper reports the progress of a research project using rock samples from a large copper–gold mining project. The orebody contains a mixture of hard rock, softer material, and clays (sericite), in proportions that are expected to vary throughout the mine-life. The feasibility of a novel comminution circuit, using an autogenous (AG) mill/scrubber and parallel trains of cone crushers and high-pressure grinding rolls (HPGR) is being investigated. The process enables the application of energy-efficient HPGR to base and precious metal hard-ores containing clay, which are usually processed using SAG mill circuits.The work presented in this paper involved laboratory testwork including pilot HPGR testing, and modelling and simulation of both the HPGR-based circuit and an equivalent SAG-based circuit. The preliminary analysis reported herein includes a comparison of the energy consumption of both circuits; complete operating and capital cost comparisons will be reported in a future paper.     

High pressure grinding rolls (HPGR) applications in the cement industry

In this study, the performance evaluation studies in five cement grinding circuits, in which HPGR is used in various configurations, were presented. Sampling surveys were performed around the circuits followed by the determination of the size distribution of the samples down to 1.8 μm using a combination of sieving and laser sizing methods. The results showed that the specific energy consumption of the circuit decreases as the size reduction achieved by the HPGR increases. As given in the case studies when the size reduction ratio (F₈₀/P₈₀) changed from 308.2 to 4.4, the specific energy consumption of the HPGR was 8.02 and 4.05 kWh/ton, respectively. Since various configurations offer rather different ball mill feeds, the best usage of HPGR could be attained by optimization of operating parameters of both ball mills and air classifiers.     

金属矿用高压辊磨机及其工艺系统发展概况

简要介绍了高压辊磨机的结构特点、发展概况及其在金属矿的应用实践;重点介绍了应用于低品位铁矿的高压辊磨机与磁力预选设备所组成的粉末预选系统的工艺概况;分析了在金属矿(尤其是铁矿)细碎作业中选用高压辊磨机应该重点考虑的设备参数和工矿条件。     

高压辊磨机挤满给料控制系统开发与应用

为了提高高压辊磨机的设备利用效率,减少空转率,本文提出了一套完整的高压辊磨机给矿控制策略。该控制策略以挤满给料专家控制算法为核心,加之对整个高压辊磨机作业回路进行故障监测与诊断,保证了高压辊磨机给料的持续和稳定性,提高了作业回路的生产效率和安全性。     

高压辊磨超细碎在贫磁铁矿石预选中的应用

从高压辊磨机的工作原理及粉碎产品特性出发,分析了高压辊磨超细碎在贫磁铁矿石预选工艺中的作用。高压辊磨机特有的层压粉碎方式使其粉碎产品具有细粒级含量高、微裂纹发育充分、解离特性好等特点。高压辊磨超细碎—预选工艺能够在贫磁铁矿石入磨前抛除大量合格尾矿,减少入磨量,提高入磨品位,降低矿石的Bond球磨功指数,提高选别效率,有利于实现节能降耗。指出今后应加强高压辊磨设备与矿石性质及生产工艺的适应性研究,发展高效、低耗的新型辊磨设备,高压辊磨机与先进的预选设备配合使用时效果更好,因此针对高压辊磨产品的特性,研发配套的先进预选设备,对提高高压辊磨超细碎—预选指标具有重要意义。     

The effect of feed moisture on the comminution efficiency of HPGR circuits

The comminution efficiency of high-pressure-grinding-rolls (HPGRs) is a well described function of a number of feed parameters including grindability, abrasion index, granulometric composition, top size and particle size distribution. Far less studied is the effect of feed moisture. This paper investigates both the overall and the specific comminution efficiency of a circuit consisting of a pilot HPGR unit followed by a batch ball mill as a function of the moisture level in the HPGR feed. Forsterite olivine sand (−7 mm) supplied by Sibelco Nordic was used as feed material. The results showed that the relationship between moisture and crushing efficiency for both the HPGR and the circuit can be described successfully by means of a parabolic function. Dry material, as well as that with the highest moisture content, showed the lowest particle size reduction ratios irrespective of the specific grinding force level. The paper also analyses the phenomenon of flake generation and shows that the feed moisture influences the flake content in the coarser size fractions of the HPGR product.