Multi-Objective Optimization for an Industrial Grinding and Classification Process Based on PBM and RSM

The grinding and classification process is one of the key sub-processes in mineral processing, which influences the final process indexes significantly and determines energy and ball consumption of the whole plant. Therefore, optimal control of the process has been very important in practice. In order to stabilize the grinding index and improve grinding capacity in the process,a process model based on population balance model(PBM) is calibrated in this study. The correlation between the mill power and the operating variables in the grinding process is modelled by using the response surface method(RSM), which solves the problem where the traditional power modeling method relies on some unobservable mechanism-related parameters. On this basis, a multi-objective optimization model is established to maximize the useful power of the grinding circuit to improve the throughput of the grinding operation and improve the fraction of –0.074 mm particles in the hydrocyclone overflow to smooth the subsequent flotation operation. The elite non-dominated sorting genetic algorithm-II(NSGA-II) is then employed to solve the multi-objective optimization problem. Finally, subjective and objective weighting methods and integrated multi-attribute decision-making methods are used to select the optimal solution on the Pareto optimal solution set. The results demonstrate that the throughput of the mill and the fraction of –0.074 mm particles in the overflow of the cyclone are increased by 3.83 t/h and 2.53%, respectively.

Data driven particle size estimation of hematite grinding process using stochastic configuration network with robust technique

As a production quality index of hematite grinding process,particle size(PS)is hard to be measured in real time.To achieve the PS estimation,this paper proposes a novel data driven model of PS using stochastic configuration network(SCN)with robust technique,namely,robust SCN(RSCN).Firstly,this paper proves the universal approximation property of RSCN with weighted least squares technique.Secondly,three robust algorithms are presented by employing M-estimation with Huber loss function,M-estimation with interquartile range(IQR)and nonparametric kernel density estimation(NKDE)function respectively to set the penalty weight.Comparison experiments are first carried out based on the UCI standard data sets to verify the effectiveness of these methods,and then the data-driven PS model based on the robust algorithms are established and verified.Experimental results show that the RSCN has an excellent performance for the PS estimation.

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Multiparameter Optimization and Controlling for Cylindrical Grinding Process

This paper bursts the bondage of conventional no-burn thought, presents an optimum strategy permitting burn appear in grinding roughing stage, but the burning layer can be summed on the following finishing stage. On the base of the basic grinding models, the objective function and constrained functions for the multiparameter optimum grinding models had been built in this paper. By the computer simulation, the nonlinear optimum grinding control parameters had been obtained, and the truth grinding process had been controlled by these parameters. The results of simulation and the experiments proved the exactitude of the optimum models and the feasibility of the optimum strategy. This paper had also created the precondition for the grinding automation, virtual grinding and intelligent grinding system for cylindrical grinding process.

Effects of the grinding process on the preparation and qualities of CWS

Two different grinding processes were examined to determine the effect grinding has on the quality of a CWS. A series of slurries was prepared from Australian (Au) and Chinese (YZ) coals. Both types of coal were ground by a Chinese (CUMT) and an Australian (JK) grinding process. The performance tests of the prepared CWS showed that fluidity of all slurries was acceptable. The concentration of the CWS from YZ coal ground by the CUMT grinding process was higher than when the JK grinding process was used. The highest concentration was 70.14% in this case. The concentration of the CWS prepared from Au coal by the JK grinding process was higher than when the CUMT grinding process was used. The highest con- centration in this case was 70.97%. These differences are caused by the particle size distribution devel- oped during the different grinding processes.

Characteristics of coal sludge slurry prepared by a wet-grinding process

Coal sludge slurry(CSS) is an alternative fuel and a potential competitive method for sludge reduction.Based on the researches of coal water slurry, we studied CSSs by using a wet-grinding process with different types of regional municipal sludge(sludge) in an orthogonal experiment. The sludge type,sludge mixing proportion, dosage of dispersant, and grinding time were tested in this study. The results show that water content and its occurrence characteristics in the sludge have primary hindering influences on slurry ability. The range of fixed-viscosity concentrations with raw wet sludge is from 50.78%to 44.40%(by weight), while the range is from 53.35% to 51.51%(by weight) with dry sludge. All of the CSSs exhibit shear-thinning behaviors with different variation trends, especially the CSSs with more than 15%(by weight) raw wet sludge in it. Adding the same proportion of raw wet sludge increases the thixotropic properties of CSSs and the highest area of thixotropy loop is 3065 Pa/s, while the highest value of dry sludge is 1798 Pa/s. Hydrophilic group plays an important role in adsorbing water and building three-dimension networks with other particles, which is the main reason for CSS properties.Therefore, the mechanism can be used to find the way for making high quality CSS.

Dynamic modeling and analysis of the closed-circuit grinding-classification process

Mathematical models of the grinding process are the basis of analysis, simulation and control. Most existent models in- cluding theoretical models and identification models are, however, inconvenient for direct analysis. In addition, many models pay much attention to the local details in the closed-circuit grinding process while overlooking the systematic behavior of the process as a whole. From the systematic perspective, the dynamic behavior of the whole closed-circuit grinding-classification process is consid- ered and a first-order transfer function model describing the dynamic relation between the raw material and the product is established. The model proves that the time constant of the closed-circuit process is lager than that of the open-circuit process and reveals how physical parameters affect the process dynamic behavior. These are very helpful to understand, design and control the closed-circuit grinding-classification process.

Experimental Determination of Optimum Exchanged Diameter in Surface Grinding Process

This paper presents an experimental study that helps to determine the optimum exchanged diameter in surface grinding. In the paper, the cost of a surface grinding process was analysed. In the cost structure, the effects of the cost parameters such as machine tool hourly rate, grinding wheel cost were taken into account. Also, process parameters including the initial grinding wheel diameter, the wheel life, the dressing regime and so on were investigated. Based on the cost structure, the set up and the procedure of the experiment for finding the optimum diameter was pointed out. From experimental results, the optimum exchanged grinding wheel diameter was found. Grinding with the optimum exchanged diameter, both the grinding cost and grinding time can be reduced significantly.

Cost Optimization of Surface Grinding Process

This paper introduces a new study on cost optimization of surface grinding. In the study, the effects of grinding parameters including the dressing regime parameters, the wheel life and the initial grinding wheel diameter on the exchanged grinding wheel diameter which were investigated. In addition, the influence of cost parameters including the machine tool hourly rate and the grinding wheel cost were taken into account. In order to find the optimum exchanged grinding wheel diameter, a cost optimization problem was built. From the results of the optimization problem, a model for determination of the optimum exchanged grinding wheel diameter was found. By using the optimum diameter, both the grinding cost and grinding time can be reduced significantly.

Grinding Process Validation Approach （gPVA）

This paper presents a load-controlled gPVA （grinding Process Validation Approach） for setting up feed-controlled CNC （Computer Numerical Control） grinding processes for the generation of optical elements. The gPVA enables the quantitative determination of process windows for CNC grinding processes as well as the identification of optimized sets of process parameters without the need to run tests on actual production parts in the industrial workshop occupying expensive CNC machining time.

Effectuate Application of Optimum Methods in Grinding Process

Random error of grinding process is central factor th at give an effect on grinding quality all through. Optimum methods are usually a pplied on grinding process for higher productivity and preferable grinding quali ty. But the grinding quality can’t be reliably controlled now and then while opt imal solution of grinding processing parameters have been applied in production, because of two involved aspects which are availability of established empirical formulas and reliability of setting up optimum mathematical model. That is to s ay, there is particular application of optimum methods in grinding process. This paper discussed that how to confirm conditions of grinding test which be po int to grinding peculiarity when test design and regression analysis are used to setting up some empirical formulas. In order to reduce effect of random errors on precision of the empirical formulas and enable them to be applied widely, a m ethod that a lot of random error can be sufficiently contained in grinding test was suggested. And then, A means to ameliorate restriction formulas of grinding quality is expounded based on marked level of the empirical formulas and improve d reliability of optimum mathematical model is given, which offer an effectual w ay for solving grinding quality out of control as a result of random error and w orkable optimal solution of grinding processing parameters can be applied in the production really. Finally, an example is presented.

Method for grinding and delaminating muscovite

A method of dry grinding muscovite based on the use of knife-mills is reported.It was possible to produce mica with a particle size below 100 and 45μm.After grinding,the samples were submitted to sonication treatment,which promoted delamination of the material.The particle size distribution shows that sonicated mica has more particles in the size range 10-50μm than does non-sonicated mica have. This also indicates a decrease in the average particle size.Characterization of the treated muscovite by scanning electron microscopy revealed a highly delaminated material with a plate-like structure.The products were characterized by chemical analysis and X-ray diffraction,too.This mica has already been used for the synthesis of pearlescent pigments.

Disturbance rejection control for Raymond mill grinding system based on disturbance observer

In the Raymond mill grinding processes,high-accuracy control for the current of Raymond mill is vital to enhance the product quality and production efficiency as well as cut down the consumption of spare parts.However,strong external disturbances,such as variations of ore hardness and ore size,always exist.It is not easy to make the current of Raymond mill constant due to these strong disturbances.Several control strategies have been proposed to control the grinding processes.However,most of them(such as PID and MPC)reject disturbances merely through feedback regulation and do not deal with the disturbances directly,which may lead to poor control performance when strong disturbances occur.To improve disturbance rejection performance,a control scheme based on PI and disturbance observer is proposed in this work.The scheme combines a feedforward compensation part based on disturbance observer and a feedback regulation part using PI.The test results illustrate that the proposed method can obtain remarkable superiority in disturbance rejection compared with PI method in the Raymond mill grinding processes.

Grinding/Cutting Technology and Equipment of Multi-scale Casting Parts

Multi-scale casting parts are important components of high-end equipment used in the aerospace,automobile manufacturing,shipbuilding,and other industries.Residual features such as parting lines and pouring risers that inevitably appear during the casting process are random in size,morphology,and distribution.The traditional manual processing method has disadvantages such as low efficiency,high labor intensity,and harsh working environment.Existing machine tool and serial robot grinding/cutting equipment do not easily achieve high-quality and high-efficiency removal of residual features due to poor dexterity and low stiffness,respectively.To address these problems,a five-degree-of-freedom(5-DoF)hybrid grinding/cutting robot with high dexterity and high stiffness is proposed.Based on it,three types of grinding/cutting equipment combined with offline programming,master-slave control,and other technologies are developed to remove the residual features of small,medium,and large casting parts.Finally,the advantages of teleoperation processing and other solutions are elaborated,and the difficulties and challenges are discussed.This paper reviews the grinding/cutting technology and equipment of casting parts and provides a reference for the research on the processing of multi-scale casting parts.

Profit Optimization of External Cylindrical Grinding

This article presents a study on profit optimization of external cylindrical grinding. In the optimization problem, the influences of several grinding process parameters such as the initial grinding wheel diameter, the wheel life, the total dressing depth as well as the effect of many cost components were investigated. A model for determination of optimum exchanged grinding wheel diameter was proposed. With this optimum diameter, a new and effective way of using the grinding wheel was proposed.

蓝宝石玻璃超声振动辅助磨削试验研究

为了探究烧结磨头不同磨头参数和磨削参数对蓝宝石玻璃磨削特性的影响,综合考虑了磨头粒度号、主轴转速、进给速度、磨削深度等因素,设计并开展了非超声和超声振动辅助磨削加工试验,研究了上述因素对蓝宝石磨削表面粗糙度、表面形貌及磨削力的影响。结果表明,超声和非超声磨削工况中,磨头粒度号增大对磨削力和表面粗糙度的影响整体均呈现先增大后减小的趋势。不同磨头粒度号工况下的超声磨削力和表面粗糙度普遍小于非超声结果,磨削力最大降幅为27.2%,表面粗糙度最大降幅为18.6%;采用粒度号200/230#的磨头进行磨削,可获得相对较小的切削力和表面粗糙度,是研究工况下的最佳粒度号,而140/170#的使用效果最差。相比于非超声磨削,超声可在所选的主轴转速、进给速度和磨削深度条件下实现磨削力和表面粗糙度不同程度的降低,在小主轴转速和小磨削深度工况下,超声磨削对蓝宝石表面质量的改善作用更显著。

复杂曲面机器人磨抛技术研究现状与趋势展望综述

在航空、能源、交通、军工等国家战略领域中,针对复杂曲面零件的自动化、高质量和高效率磨抛需求,对近年来国内外工业机器人磨抛加工关键技术及集成系统的研究和应用进展进行了综述。首先,从复杂曲面机器人磨抛机理及工艺优化、磨抛运动轨迹规划、磨削力控制等方面总结了复杂曲面机器人磨抛技术的研究成果;然后,介绍了国内外机器人磨抛集成系统应用现状;最后,分析了复杂曲面机器人磨抛技术的主要问题以及发展趋势,为该技术的发展提供了重要的指导和方向。研究结果表明:当前该技术存在的主要问题包括磨抛机理不够清晰,数学模型不够准确,复杂曲面机器人磨抛轨迹规划效率不高,磨抛力的控制仍不够精准等;另外,磨抛工艺参数优化、机器人力位混合控制、机器人高精度标定与误差补偿、基于数字孪生的机器人磨抛在线监控、机器人磨抛细分应用场景等方面的研究和实践将极大地推动机器人磨抛技术的发展和应用。

中药炮制学课程思政元素挖掘及教学设计案例分析

思政教学与专业教育的有机融合,不仅可以强化教师“立德树人”的教育理念,更能实现全程育人、全方位育人的教育目标。这就需要在实践过程中,根据中药学专业人才培养目标,深入挖掘课程思政元素,优化教学设计,创新教育教学方法,实现课程思政在中药学专业教育的全过程融入。本教学改革以水飞法为例,从思政元素的挖掘、思政元素映射与融入点的切入、教学方法的创新、思政教育的拓展与评价等方面进行了优化设计,深入挖掘课程思政教学内容和实现方式,并有效应用于教学实践过程,以期构建价值引领、知识传授、能力培养有机统一的中药炮制学教学模式,为中药学类专业课程思政建设及人才培养模式的改革提供借鉴参考。

带式焙烧机配建200万吨磨矿生产线设计特点

介绍了某200万吨/a带式焙烧机球团磨矿生产线的设计特点。通过对原矿特性和球团生产需求的研究,确定采用先进的两段湿式闭路磨矿生产工艺,最终产品为粒度-200目以下≥95%,水分≤9%的赤铁精矿。设计过程中,集成应用了多项先进设备,如溢流型球磨机、立磨机、高效浓密机、快开板框压滤机等,并充分考虑了节能环保因素,生产能耗低,噪音污染小,无生产污水和固体废弃物外排。本工程的建成为带式焙烧机生产的原料供应提供了新的思路。