Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Модель руху матеріалу в проточній частині барабанного млина

Стаття присвячена актуальній проблемі моделювання руху матеріалу в проточній ча-стині барабанного млина. Задача – встановлення шляхом аналітичного моделювання взаємо-зв'язку між витратою пульпи і її рівнем в місці завантаження барабанного млина. Встановлену залежність рекомендується використовувати при визначенні оптимальних режимів роботи млина для отримання готового продукту подрібнення із заданими фізико-механічними властивостями.Статья посвящена актуальной проблеме моделирования движения материала в про-точной части барабанной мельницы. Задача - установление путем аналитического моделирования взаимосвязи между расходом пульпы и ее уровнем в месте загрузки барабанной мельницы. Установленную зависимость рекомендуется использовать при определении опти-мальных режимов работы мельницы для получения готового продукта измельчения с задан-ными физико-механическими свойствами.The article is devoted to the actual problem of modeling the movement of material in the flowing part of a drum mill. The task is to establish, through analytical modeling, the relationship between the pulp flow rate and its level at the point of loading of the drum mill. The established dependence is recommended to be used at definition of optimum operating modes of a mill for reception of a finished product of crushing with the set physicomechanical properties

Математична модель проходження матеріалу через розвантажувальні грати барабанного млина

Стаття присвячена актуальній проблемі моделювання барабанного млина, зокрема, явищ у розвантажувальній частині. Описана якісна і кількісна картина проходження мате-ріалу через розвантажувальні грати млина. Запропонована математична модель може бу-ти використана як наукова база для розрахунку конструктивних і технологічних парамет-рів розвантажувальних грат барабанного млина.Статья посвящена актуальной проблеме моделирования барабанного мельницы, в частности, явлений в разгрузочной части. Описанная качественная и количественная кар-тина прохождения материала через разгрузочную решетку мельницы. Предложенная ма-тематическая модель может быть использована как научная база для расчета конструк-тивных и технологических параметров разгрузочных решеток барабанной мельницы.The article is devoted to the actual problem of simulation of the drum mill, in particular, phe-nomena in the unloading part. The described qualitative and quantitative picture of the passage of material through the grate discharge grate. The proposed mathematical model can be used as a sci-entific basis for calculating the design and technological parameters of the drum grinding drum un-loading grids

On-line sensors for measuring the total ball and charge level in tumbling mills

Includes bibliographical references.Tumbling mills are still the mostly used milling device in the mineral processing industry for both coarse and fine grinding applications. A number of factors affect the performance of tumbling mill. One of these factors is volumetric filling which is the volume of charge in the mill expressed as a fraction of the total volume available. The volumetric filling controls the mill throughput, power draw and product size. The common method of measuring volumetric filling is by taking in situ measurements when the mill is stationary. This method is disruptive to production due to the mill downtime involved. The use of on-line sensors for measuring the volumetric filling using acoustic, inductive proximity and conductive sensors are the new technologies attempting to monitor volumetric filling in situ. The methods are non-intrusive and low cost approach for direct monitoring of dynamic volumetric filling conditions in the tumbling mill. The dynamic volumetric filling was assumed to be directly related to static mill filling conditions. In this study, the volumetric filling was calculated from the toe and shoulder angles estimated by the CSIRO monitor (acoustic) and the Magotteaux Sensomag (inductive proximity and conductive) sensors. The CSIRO acoustic sensor was installed on a run-of-mine (RoM) ball mill at Angloplatinum UG2 Concentrator at Rustenburg, South Africa. The toe and shoulder angles were obtained from the surface vibration caused by the impact of the charge on the mill shell. The industrial scale experiments were performed at varied mill feed rate at constant ball load of 28%. In the pilot scale experiments, the Magotteaux ball mill at Frank Concentrator was equipped with a Sensomag sensor for measuring the toe and shoulder angles of the slurry and ball load based on the principle of conductance and induction, respectively. The mill was configured to operate as a RoM ball mill. The experiments were conducted at varying mill speeds (75%-85% critical speed), feed rate (1200-2800kg/hr) and ball loads (15-26%). The static mill filling was determined from physical measurements after crash stopping the mill

Measuring, characterisation and modelling of load dynamic behaviour in a wet overflow-discharge ball mill.

Overflow ball mills have found popular application in the ore dressing process for post-primary grinding firstly owing to their ability to produce finer grinds, necessary for efficient mineral liberation and better flotation recovery and secondly due to lower initial capital outlay. However they are inefficient and intensive energy consumers. This trend has been exacerbated in the wake of increased installation of large diameter ball mills to benefit from economies of scale, coupled with diminishing ore quality currently being experienced by mines worldwide. To fully utilise the available mill capacity and achieve optimal performance whilst maintaining energy efficiency for these large devices, closer and more effective control is needed. Satisfaction of this need would result in stability of the entire mineral processing circuit, thereby reducing the overall cost in mineral extraction. Clear and deeper understanding of the in-mill behaviour is fundamental to the realisation of the above objective. This thesis explores several experimental and modelling techniques to obtain deeper understanding of the internal behaviour of an overflow ball mill. A direct load sensor comprising an inductive proximity probe and a conductivity probe installed through the mill shell has been utilised to collect information of the media and slurry dynamic positions inside a laboratory ball mill while a commercial on-line ball and pulp sensor was employed to collect similar information on an industrial overflow ball mill. Useful insights were acquired that can help the design of control strategies for optimal mill performance. Four feature variables, i.e. dynamic media angle, slurry pool angle, conductivity signal amplitude and the slurry pool depth, derived from the sensor signals data were characteristically influenced by changes in mill operational conditions. Therefore the possibility of using these features to predict the associated mill operational variables is feasible. In view of the findings, two multivariate models, one based on the concept of data projection to latent space (PLS) and the other combining PLS and radial basis functions neural networks (RBF) were built and applied to predict the in-mill slurry density and ball load volume. Both models yielded adequate predictions, albeit the hybrid PLS-RBF model displayed marginally better prediction performance. The results are indicative of the available potential for mill on-line monitoring and control by multivariate techniques based on relevant features contained in the media and slurry sensor signals data. In another endeavour, a gamma camera was successfully employed to study the flow and mixing behaviour of slurry inside a laboratory mill using Technetium-Tc99m radiotracer as a flow follower. The effects of slurry viscosity and mill rotational speed on slurry mixing rate within the ball charge and slurry exchange rate between the pool and the ball charge were assessed, yielding insightful data. However, the results remain inconclusive as only qualitative information could be obtained owing to the radiation attenuation effects by the steel ball charge. In the quest to improve the understanding of material transport inside the mill, the data acquired on an industrial mill through salt tracer tests was adequately analysed to assess the variation of slurry residence time distribution (RTD) and volumetric holdup inside the mill as affected by changes in slurry concentration and ball load volume. A model based on the concept of serial stirred mixers with a plug flow component produced fairly accurate predictions of the RTD data. Also, equations derived from a mathematical description of the dynamic load profile produced good estimates of the in-mill slurry volumetric holdup. Further, an improved mixing-cell model was developed and applied to characterise the in-mill slurry hydrodynamic transport based on the measured RTD data. The model was able to account for the effects of non-ideal flow conditions such as slurry back-mixing, slurry exchange between the pool and ball charge and bypass flows on the main flow of slurry thus giving correct description of the inherent in-mill slurry transport dynamics. Note that failure to tune the mill appropriately to achieve desirable in-mill slurry transport behaviour may result in poor milling performance and corresponding high energy expenditure. Thus, the results obtained in this thesis clearly demonstrate that, a combination of experimental techniques and mathematical models is a viable route to enhance understanding of mill internal behaviour, which in turn enables development of better control schemes for optimal mill performance

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

XVIII International Coal Preparation Congress

Changes in economic and market conditions of mineral raw materials in recent years have greatly increased demands on the ef fi ciency of mining production. This is certainly true of the coal industry. World coal consumption is growing faster than other types of fuel and in the past year it exceeded 7.6 billion tons. Coal extraction and processing technology are continuously evolving, becoming more economical and environmentally friendly. “ Clean coal ” technology is becoming increasingly popular. Coal chemistry, production of new materials and pharmacology are now added to the traditional use areas — power industry and metallurgy. The leading role in the development of new areas of coal use belongs to preparation technology and advanced coal processing. Hi-tech modern technology and the increasing interna- tional demand for its effectiveness and ef fi ciency put completely new goals for the University. Our main task is to develop a new generation of workforce capacity and research in line with global trends in the development of science and technology to address critical industry issues. Today Russia, like the rest of the world faces rapid and profound changes affecting all spheres of life. The de fi ning feature of modern era has been a rapid development of high technology, intellectual capital being its main asset and resource. The dynamics of scienti fi c and technological development requires acti- vation of University research activities. The University must be a generator of ideas to meet the needs of the economy and national development. Due to the high intellectual potential, University expert mission becomes more and more called for and is capable of providing professional assessment and building science-based predictions in various fi elds. Coal industry, as well as the whole fuel and energy sector of the global economy is growing fast. Global multinational energy companies are less likely to be under state in fl uence and will soon become the main mechanism for the rapid spread of technologies based on new knowledge. Mineral resources will have an even greater impact on the stability of the economies of many countries. Current progress in the technology of coal-based gas synthesis is not just a change in the traditional energy markets, but the emergence of new products of direct consumption, obtained from coal, such as synthetic fuels, chemicals and agrochemical products. All this requires a revision of the value of coal in the modern world economy