A specific energy-based size reduction model for batch grinding ball mill

A particle size reduction model has been developed as the first component of an upgraded ball mill model. The model is based on a specific energy-size reduction function, which calculates the particle breakage index, t₁₀, according to the size-specific energy, and then calculates the full product size distribution using the t₁₀–t_n relationships and the mass-size balance approach. The model employs an ore-specific and size-dependent breakage function, whose parameters are independently measured with a fine particle breakage characterisation device, the JKFBC. This has effectively overcome the limitation of using a default breakage appearance function for all ores in the perfect mixing ball mill model. Since the ore-specific characteristics and the machine-related specific energy parameters are mechanistically incorporated in the size reduction model, it has the capability to predict size reduction in response to changes in the ball mill feed breakage characteristics and the operation-related specific energy.     

Multi-component AG/SAG mill model

The JKMRC has been studying and modelling industrial AG and SAG mills for over 40 years, but the ability to simulate the effects of blending hard and soft components on mill performance remains quite limited. In an effort to quantify these effects for modelling purposes, a series of laboratory, pilot scale and full scale tests, using multi-component feeds were conducted under the AMIRA P9O project.The obtained data shows a non-linear trend between the measured mill throughput and the proportion of soft component in the feed, as well as the effect of fresh feed composition in mill product size distribution and load. Therefore, a new multi-component AG/SAG mill model structure was developed to account for these observed effects, and it was validated using pilot and full scale data.     

Fundamental discrete element charge motion model validation

With improving and faster computers, research into understanding the complex interactions of mineral processes is now a practical proposition for aiding design and optimization. In comminution research, recent trends have been made to describe internal dynamics of mills and relate them to such things as power draw [1–3]. In this work, a charge motion model is described that takes advantage of the empirical approach of Morrell while being anchored in the fundamentals of discrete element models such as those of Inoue and Mishra/Ramani. In this present work, a fundamental discrete element ball charge motion model is defined with the help of an arbitrary discretization scheme of the charge. The model is then calibrated and validated using two ball mill data sets with simulated power being compared with observed power. Further, this technique permits charge motion to be calculated while determining a frequency distribution of impacts for any given mill be it grate or overflow discharge.     

Application of model predictive control in ball mill grinding circuit

Grinding circuit needs to be stably controlled for high recovery rate of mineral ore and significant reduction of production cost in concentrator plants. Ball mill grinding circuit is essentially a multi-input–multi-output (MIMO) system with strong coupling among process variables. Simplified model with multi-loop decoupled PID control usually cannot maintain a long-time stable control in real practice. The response tests between four controlled variables (namely, product particle size, mill solids concentration, sump level and circulating load) and four manipulated variables (namely, fresh ore feed rate, mill feed water flow rate, pump speed and dilution water flow rate) are carried out to construct a four-input–four-output model of grinding circuit. Based on this modeling, constrained model predictive control (MPC) is adopted to handle such strong coupling system and evaluated in an iron ore concentrator plant. The variables are controlled around their set-points and a long-term stable operation of the grinding circuit close to their optimum operating conditions is achieved. More than three years’ operation in industry demonstrates the effectiveness and practicality of this control strategy.     

Inferential measurement of sag mill parameters IV: Inferential model validation

This paper discusses a case study application of inferential measurement models for semiautogenous grinding (SAG) mills and is the fourth paper in a series of five papers on inferential measurement of SAG mill parameters. The development of the inferential measurement models of SAG mill discharge and feed streams and mill rock and ball charge levels, detailed earlier in the series, is summarised here. The models are then tested on plant data for validation and analysis. Model characteristics are explored to highlight model sensitivity and relative uncertainty. The results are encouraging while limitations are noted and potential avenues for further research are discussed.     

球磨机衬板在一段磨机上的应用

介绍了近十年金岭铁矿球磨机衬板在一段磨机上的的使用情况，通过对比分析，总结出磨机衬板的理想组合，从而达到节能、增效的目的。     

Analysis and validation of a run-of-mine ore grinding mill circuit model for process control

A simple and novel non-linear model of a run-of-mine ore grinding mill circuit, developed for process control and estimation purposes, is validated. The model makes use of the minimum number of states and parameters necessary to produce responses that are qualitatively accurate. It consists of separate feeder, mill, sump and hydrocyclone modules that can be connected to model different circuit configurations. The model uses five states: rocks, solids, fines, water and steel balls. Rocks are defined as too large to be discharged from the mill, whereas solids, defined as particles small enough to leave the mill, consist of out-of-specification coarse ore and in-specification fine ore fractions. The model incorporates a unique prediction of the rheology of the slurry within the mill. A new hydrocyclone model is also presented.The model parameters are fitted to an existing plant’s sampling campaign data and a step-wise procedure is given to fit the model to steady-state data. Simulation test results of the model are compared to sampling campaign data of the same plant at different steady-state conditions. The model shows promise in estimating important process variables such as mill power and product particle size and is deemed suitable for process control studies.     

模型和参数识别理论与方法

利用现代控制理论和系统论的观点,结合位移反分析方法,研究了地下开采引起的岩层与地表移动的模型识别和参数识别的理论与方法,为解决岩层与地表移动数值计算的关键问题提供了新途径.     

Measurement system of the mill charge in grinding ball mill circuits

Investigation of a dry fine grinding circuit has shown significant influence of the mill load (powder filling) on the production capacity. To improve the circuit performance at industrial scale, alternative ways of mill load measurement were investigated. Detection of strain changes in the mill shell during mill rotation, by using a piezoelectric strain transducer, provided very interesting results, allowing evaluation of the weight of the mill charge and control of the powder filling to obtain an optimal level. Power draw has thus been increased by about 5% compared to the old configuration where mill motor power input was used to control the mill charge. By measuring mechanical vibration with the transducer, additional useful information has been obtained about the behavior of the cataracting and cascading balls inside the mill shell. Finally an important factor was simplicity and low investment cost of the total installation, as many fine grinding mills operate in relatively small circuits that do not warrant large investment for alternative measurement methods.     

Benefits of optimisation and model predictive control on a fully autogenous mill with variable speed

Autogenous (AG) milling is utilised around the world for particle size reduction. The system exhibits highly non-linear behaviour in addition to being subject to unmeasured variability associated with most ore bodies. Anglo American Platinum aimed at improving online optimisation of the circuit by implementing industrial model predictive control (MPC) to reduce system variability and continuously drive towards the optimal operating point within system constraints.The industrial dynamic matrix controller commissioned on the AG mill with a variable speed drive resulted in a 66% reduction in power and a 40% reduction in load standard deviation. These are the main controlled variables of the mill. The controller also improved the objective function, effective power utilisation, by 11%. This reduction in operated variable variability enabled a test campaign where the mill was controlled at various operating regions in order to establish the conditions conducive to the finest product size at a given mill feed rate.Moving the mill operating region from the benchmarked plant to the optimal grind environment and stabilising the mill at this point with the model predictive controller provided an estimated potential recovery increase of 0.32% (absolute) due to better liberation.     

基于破碎理论下球磨机功耗模型预测研究

在分析国内外几种功耗理论的基础上,基于磨矿介质在球磨机中的运动规律,推导出了单位物料破碎研磨能量公式。并以此破碎研磨公式为基础提出了球磨机单位功耗模型公式。在磨机功耗模型基础上,推导出了磨机理论需求功率公式。以锡石多金属硫化矿矿石为原料,研究磨矿时间对矿石破碎率的影响规律,利用实验室获取的实际磨矿试验数据,研究分析比较了在相同磨矿条件下的Bond单位功耗、磨机理论单位功耗、磨机功耗模型单位功耗三种计算结果,结果表明计算出的磨机功耗模型单位功耗与磨机理论单位功耗非常接近,相对误差仅2.06%,证明提出的球磨机单位功耗模型具有较好的适用性与可靠性。     

Predicting the effect of operating and design variables on breakage rates using the mechanistic ball mill model

Batch grinding tests have been a very good tool to aid in understanding the effect of design and operating variables in ball milling, as well as in providing data for a couple of successful scale-up methods. Recently, a mechanistic model of the ball mill has been proposed, and the present paper describes its application in the simulation of batch mills operating under a range conditions. First-order breakage rates have been estimated using data from these simulations, and used to investigate the effect of operating and design variables in milling. Predictions using the mechanistic model are then compared to those using the scale-up relationships proposed by Austin and collaborators and Herbst and Fuerstenau. The trends predicted using the mechanistic model are in general agreement with the empirical models. Good correlation has also been observed between the simulated specific breakage rates and the specific mill power, which is in agreement with the scale-up method proposed by Herbst and Fuerstenau.     

Validation of a model for physical interactions between pulp,charge and mill structure in tumbling mills

Modelling the pulp fluid and its simultaneous interactions with both the charge and the mill structure is an interesting challenge. The interactions have previously been modelled for dry grinding with a combination of discrete element method (DEM), smoothed particle hydrodynamics (SPH) and the finite element method (FEM), where the DEM particles or SPH particles represent the grinding balls and FEM is used to model the mill structure. In this work, the previous model is extended to include fluids with SPH. Wet milling with water and a magnetite pulp, for graded and mono-size charges are numerically modelled and validated. The internal working of the charge and the physical interaction between the charge and the mill structure is studied. The combined SPH–DEM–FEM model presented here can predict the classical DEM results, but can also predict responses from the mill structure, as well as the pulp liquid flow and pressure. Validation is conducted by comparing numerical results with experimental measurements from grinding in an instrumented small-scale batch ball mill equipped with an accurate torque metre. The simulated charge movement is also compared with high speed video of the charge movement for a number of cases. Numerical results are in good agreement with experimental measurements.     

Use of the attainable region method to simulate a full-scale ball mill with a realistic transport model

Optimisation and better control of milling circuits require extensive modelling of milling data. This paper extends the enquiry to the use of the attainable region (AR) technique to determine the optimal residence time of ore in a ball mill. It also evaluates the energy requirements of the mill at the set residence time to maximise the production of the desired size range which enables maximum recovery of platinum group minerals (PGM) during the flotation stage.With these purposes in mind, the breakage function and the scaled-up selection function parameters were used to simulate the operating conditions required by an industrial ball mill and the power requirements were predicted using the Morrell power model. This allowed the application of the AR methodology to be extended to a full-scale ball mill. Then a link was established between residence time to mill product specifications for a given feed size.The findings showed that the residence time required by a full-scale mill falls between those at which the fully mixed and the plug flow mills operate. The results also showed that operating the ball mill at a lower mill speed and a higher ball filling saves energy. Mill speed was again found to be a key operational factor for controlling the retention time of particles inside the mill. This yielded valuable insight for the importance of optimally controlling both the residence time of the material inside the mill and the amount of energy required to maximise the desired size range, in this case −75 + 9 μm.     

高效节能型管磨机

为了降低水泥粉磨的能耗,针对管磨机的工作特点,对其整体结构进行了创新性设计和优化,提出了高效节能型管磨机,并应用于实践,取得了较好的效果。     

塔磨机技术综述

塔磨机是一种新型湿式细磨和超细磨设备,该设备在选矿厂碎磨车间和烟气脱硫石灰石浆液制备等领域逐渐得以应用.本文主要介绍了国内外塔磨机的发展状况、粉磨机理、主要结构及各部件之间的装配关系,以及塔磨机常用的工艺位置、给料和排料颗粒粒度和工艺流程.     

Experimental analysis of wet mill load based on vibration signals of laboratory-scale ball mill shell

Real-time measurement of the mill load is the key to improve the production capacity and energy efficiency for the grinding process. In this paper, experimental analysis of the wet mill load based on the vibration signals of the laboratory-scale ball mill shell is presented. A series of experiments are conducted to investigate the vibration characteristics corresponding to different grinding conditions such as dry grinding, wet grinding and water grinding. The power spectral density of the vibration signals is systematically interpreted.Experimental results show that the rheological properties of the pulp affect the amplitude and frequency of the vibration signal. The most important conclusion is that the frequency range of the shell vibration of the laboratory wet mill can be divided into three parts, namely natural frequency band, main impact frequency band and secondary impact frequency band. Finally, soft-sensor models between vibration signal and mill operating parameters of mill load are established using genetic algorithm-partial least square (GA-PLS) technology. After more work on industry scale ball mill is done, the soft-sensor modeling based on the mill shell vibration for operating parameters of mill load will improve the performance of the ball mill in the grinding process.