Search Documents

By M. J. Laurila

On-line analyzers have made possible the use of Fuzzy Logic Control (FLC) for local control applications in coal preparation plants. This includes FLC control of complete circuits such as heavy media vessels, cyclones and froth flotation. These circuits can be controlled in real time in a feedback control loop with an on-line analyzer. Control strategies can be readily developed using Statistical Process Control (SPC) techniques which are first applied off-line in manual mode through the use of control charts and then this process is brought on-line using FLC in conjunction with an on-line analyzer to fully automate the circuit. This paper outlines the types of control strategies employed and presents examples of automatic verses manual control.

Jan 1, 1997

By M. J. Laurila

On-line analyzers have made possible the use of fuzzy logic control (FLC) for local control applications in coal preparation plants. This includes FLC of heavy media vessels, cyclones and froth flotation. These circuits can be controlled in real time in a feedback control loop with an on-line analyzer. Control strategies can be developed using statistical process control (SPC) techniques that are first applied offline in manual mode through the use of control charts. This process is then brought on line using FLC in conjunction with an on-line analyzer to automate the circuit. The advent of programmable logic controllers into preparation plants has enabled the implementation of regulatory control. As shown in Fig. 1, regulatory control is the first level of process control as applied in a processing facility. This involves: ? The logic sequences for start-up and shutdown procedures and all the necessary interlocks for safety purposes. ? The systems to control individual parameters and individual units. Various sensors provide information that is useful to plant operators, while some can be used as signals to simple control loops (Couch, 1996). This is the foundation of process control. It must be performed well if there is to be any success in supervisory control (level 2). Supervisory control involves overseeing and directing the operation of unit operations, or of the whole plant. This includes more complex loops with cascade control. And it may involve feed forward and feedback systems. There have been some applications of this kind of control to thickeners and flotation circuits in coal preparation plants. In addition, there are supervisory controls on some dense medium circuits and, in a few cases, on jigs. These are implemented with proportional integral- derivative (PID) controllers that are available in the PLC or distributed control system (DCS) operating soft ware. In a coal preparation plant, there might exist 200 to 400 PID loops. In a coal-pro¬cessing plant, this number is increased to 2,000 loops or more. It is important to use the correct algorithm or function to control a process variable to the point where automatic control shows a markedly decreased variability over manual mode. This is where fuzzy logic and neural networks have an advantage over traditional model-based expert systems. Because dynamic models of coal preparation unit operations do not exist, model-based expert systems that are prevalent in minerals processing cannot work. Not enough is known about the dynamics of the gravity separation processes employed in coal preparation. Therefore, an artificial intelligence (AI) system consisting of a subset of fuzzy logic, genetic algorithms and neural networks must be applied in coal preparation plants if a supervisory control system is to be successful across a range of feed characteristics and variable set points.

Jan 1, 1997

By K. Rajamani, I. Shah

The development of liquid-level control algorithms, based on sets of linguistic rules expressing human operator's "intuitive" control strategies, have been reported. The main objective of the present paper is to illustrate the implementation methodology. The experimental work was done with a 28.3Lflotation cell. The control variable (height of pulp in the cell) was controlled by manipulating the outflow rate. The controller algorithms were programmed and implemented using an Applelle computer and a Keithley das Series 500 measurement and control interface. It is pointed out that the scheme of fuzzy controllers is simple to use and powerful enough to handle complex and nonlinear systems.

Jan 1, 1987

By T. Neesse

In many cases, the use of hydrocyclone control is desirable for the stabilization of separation in the setting of changing feed conditions. Control concepts based on exact mathematical models are not satisfactory due to the complexity of the physical process. In this case, fuzzy control is a suitable solution. The data are primarily derived from an optical sensor that monitors the outside view of the free underflow stream. A throttling valve, serving as an actuator, is installed in the overflow pipe that regulates the volume split of the cyclone. Applications in closed circuit grinding and in separation plants for tunnel driving, fine sand dewatering, and classification of kaolin demonstrate the typical use of this development. Additionally, the technological characteristics of the cyclone may be improved by this control, which is mainly caused by the increased discharge capacity of the un-der flow nozzle. A further advantage is the option to operate at an optimal operation point. In many cases, this point is located at the transition spray/rope discharge. The improved operation characteristics present new options for extensive applications of fuzzy cyclone control.

Jan 1, 2014

By Hamed Khodadadi, Hamid Ghadiri

In this study, a fuzzy logic self-tuning PID controller based on an improved disturbance observer is designed for control of the ball mill grinding circuit. The ball mill grinding circuit has vast applications in the mining, metallurgy, chemistry, pharmacy, and research laboratories; however, this system has some challenges. The grinding circuit is a multivariable system in which the high interaction between loops, the variation of the system parameters with time, and time delay are some of the problems that pose a challenge. Since the controller parameters are determined offline in classic PID control, these gains are unchangeable and cannot overcome the mentioned challenges in this system. Hence, a fuzzy logic self-tuning PID controller, which is a combination of fuzzy logic and a conventional PID controller, is proposed to control the grinding system, especially in the presence of model mismatch and disturbances. In addition, in order to solve the system challenges, a multivariable control approach based on an improved disturbance observer is proposed to suppress the effects of the disturbances. The most important feature of the algorithm proposed in this paper as the combination of fuzzy logic self-tuning PID and improved disturbance observer is its ability to eliminate system interaction, attenuate internal and external disturbances, and compensate the effect of system uncertainty on the performance of the ball mill grinding circuit. Simulation results in the cases of the set-point change in particle size and circulating load in the presence of model mismatch and external disturbances confirmed the controller performance compared to other controllers.

By Hamed Khodadadi, Hamid Ghadiri

In this study, a fuzzy logic self-tuning PID controller based on an improved disturbance observer is designed for control of the ball mill grinding circuit. The ball mill grinding circuit has vast applications in the mining, metallurgy, chemistry, pharmacy, and research laboratories; however, this system has some challenges. The grinding circuit is a multivariable system in which the high interaction between loops, the variation of the system parameters with time, and time delay are some of the problems that pose a challenge. Since the controller parameters are determined offline in classic PID control, these gains are unchangeable and cannot overcome the mentioned challenges in this system. Hence, a fuzzy logic self-tuning PID controller, which is a combination of fuzzy logic and a conventional PID controller, is proposed to control the grinding system, especially in the presence of model mismatch and disturbances. In addition, in order to solve the system challenges, a multivariable control approach based on an improved disturbance observer is proposed to suppress the effects of the disturbances. The most important feature of the algorithm proposed in this paper as the combination of fuzzy logic self-tuning PID and improved disturbance observer is its ability to eliminate system interaction, attenuate internal and external disturbances, and compensate the effect of system uncertainty on the performance of the ball mill grinding circuit. Simulation results in the cases of the set-point change in particle size and circulating load in the presence of model mismatch and external disturbances confirmed the controller performance compared to other controllers.

By Hamed Khodadadi, Hamid Ghadiri

The ball mill grinding circuit has widespread application in mining, metallurgy, chemistry, pharmacy and research. It faces some challenges because a grinding circuit is a multivariable system in which high interaction between loops, variation of system parameters with time, and time delays are problems. In this study, a fuzzy logic self-tuning proportional–integral–derivative (FLST-PID) controller based on an improved disturbance observer is designed for control of ball mill grinding circuits. It is combined with an improved disturbance observer (IDOB) to eliminate system interaction, attenuate internal and external disturbances and compensate the effect of system uncertainty on the performance of the ball mill grinding circuit.

By J. A. Meech, C. A. Harris

"The application of control theory in mineral processing is more difficult than in other industries because of the complex nature of the unit processes involved and because of problems with accurate on stream measurement of process variables. Conventional control is based on proportional, integral and derivative functions of a continuously measured error term. Computer control can enhance these actions by incorporating logical routines to switch from one relationship to another. The success of this logical approach depends on our understanding of the process dynamics and the stability of the process and model under all conditions. Typically the model does not apply at all times in mineral processing because of frequent and unmeasurable changes in the ore parameters.Recent advances in the theory of fuzzy sets have led to the application of this science to process control. Fuzzy Logic can be used to develop heuristic or rule-of-thumb controllers with the strategy based on the actual operating practice of experienced plant operators. Control action has increased flexibility through the adaptation of human reasoning. Acceptance of the control system by operating personnel is significantly higher because of their participation in its formulation. The requirement of an exact model is not essential.A heuristic controller has been designed and tested with a computer simulation model of a secondary crushing plant. The results of this study are discussed and future applications of this control technique to other mineral processes are suggested. IntroductionThe application of control theory in mineral processing is more difficult than in other industries because of the complex nature of the unit processes involved. Mineral processes typically are characterized by non-linear relationships between input and output variables. Many of these variables cannot be monitored accurately on-stream and so long time lags on the measurement loop are features of the system. The processes, themselves, often have long time-varying responses while the process loads fluctuate significantly on a short-term basis.Attempts to control these processes have led to the formulation of mathematical models to describe each unit activity. Adaptive techniques have also been tried to compensate and account for process changes and vageries. These approaches are mathematically rigorous so that their complexity and precision limit their usefulness when applied to ""vague"" processes."

Jan 1, 1987

By M J. Pejovic, I Miljanovic, A Milutinovic4, T Benovic, A Petrovski

The paper presents a model of a multigrade monitoring-management structure for support to decision making and management in real and extended time in mineral processing (MP). The model was created as a result of a long-lasting research, design and development of mining, computer integrated monitoring-management systems. Apart from the general explanations, the authorsÆ state in the introduction that efficiency of a system for support to decision-making and management in mineral processing is more difficult to achieve by conventional approaches, than by the fuzzy logic approach. Starting from the multiphase structure of process flows in MP, the following are process and monitoring-management oriented graphs. The graphs served as a foundation of the multigrade hierarchical fuzzy model for support to decision making and management in MP. Following the example of the monitoring-management system of the æRudnikÆ mine flotation plant, fuzzy logic implementation was shown. The key conclusions of the paper are that fuzzyfication of layers of the decision making and management model has full justification due to the complexity and dynamics of mineral processing processes, complications and often insurmountable difficulties concerning the precise description of real systems by conventional mathematical tools, variability of external influences, and the (general) non-linearity of the MP processes management criteria functions.

Sep 26, 2011

By C. L. Karr

Researchers at the University of Alabama have developed a method for producing fuzzy linguistic models of mineral processing equipment directly from engineering data. These fuzzy linguistic models rely exclusively on data collected from the processing systems being modeled and do not presuppose an understanding of the physics of the system. The fuzzy linguistic models use descriptive rules and explicit membership functions that provide a precise, nonmathematical description of the processing equipment. A genetic algorithm is employed to simultaneously select rules and tune membership functions used in the fuzzy models. The result is an extremely flexible approach to modelling that is applicable in a variety of linear and nonlinear systems. The effectiveness of this approach to modelling is demonstrated using a four-input, two-output model of a grinding circuit.

Jan 1, 1996

By C. L. Karr, D. L. Meredith, D. A. Stanley

The U.S. Bureau of Mines is currently investigating ways to combine the learning capabilities of genetic algorithms with the process control capabilities of fuzzy logic. Fuzzy logic has been successfully used for controlling a number of physical systems. However, the selection of acceptable fuzzy membership functions has generally been a subjective decision. In this paper, high-performance fuzzy membership functions are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than the membership functions selected by the authors for the liquid level system considered. The approach to developing genetic algorithm-based fuzzy logic controllers is demonstrated on a liquid level controller.

Jan 1, 1990

By Cong Zhang, Huaying Wang, Yixin Wei

"Water inrush is a serious geological accident in underground coal mines. This paper focuses on the method of the bow tie analysis based on fuzzy reliability to assess the risk of water inrush in coal mines. First, post failure probability and repair probability of initiating events are divided into 5 levels. Then triangular fuzzy numbers are adopted to quantify experts’ language and to acquire the reliability rate which close to the actual values by defuzzification and calculation. According to dynamic bow-tie analysis model, using the method of moments to fit the reliability time of events by Weibull distribution and offering the random sampling rule of failure and repair time for illustrating the feasibility of fuzzy reliability evaluation. To demonstrate the effectiveness of the proposed assessment approach, bow tie analysis model of water inrush in coal mines is taken as an example.Introduction Dynamic bow tie (DBT) analysis is composed of dynamic fault tree and dynamic event tree analysis, and considers the impact of the time factor upon risk assessment of a system. There are many algorithms applied to calculation of the probabilities of node accident and accident consequence of dynamic bow tie analysis: Hidden Markov Model, Bayesian Network (Khakzad et al 2013), Integral Algorithm (Amari et al 2003) and Monte Carlo Simulation (Kim et al 2016). In terms of simulated time and practicability, the Monte Carlo Simulation has an advantage over other methods. DBT requires mass data in quantitative analysis, including the failure rates and the repair rates of the basic events of the Fault Tree (FT) and the subsequent events of the Event Tree (ET) at different time points, i.e., the distribution of failure time and repair time. In practical analysis, it is hard to obtain a large amount of exact historical statistical data, which is a major problem of risk assessment. Due to the difficulty of obtaining the exact data and historical failure data of the basic events and the subsequent events, the FT and ET analysis is stuck with the study of minimal cut sets, minimal diameter sets, structural importance and qualitative analysis (Liu and Zhang 2010, Yan et al 2012, Wang et al 2009, Li and Wang 2011). This paper will use fuzzy numbers and the defuzzification method to transform the experts’ language into the failure rates and repair rates of basic events and subsequent events, solving the problem that it is difficult to obtain a large amount of historical statistical data, and will use the method of moment to conduct Weibull fitting of the reliability time to provide the random sampling criteria of event failure and repair time in Monte Carlo simulation."

Jan 1, 2017

By I. Bakry

Uncertainty is an inherent characteristic of construction projects. Neglecting uncertainties associated with different input parameters in the planning stage could well lead to misleading and/or unachievable project schedules. The objective of this paper is to present a new approach towards scheduling repetitive construction projects while accounting for uncertainty. The paper presents an algorithm that quantifies anticipated delays resulting from different sources of uncertainty in the form of fuzzy time buffers. Through inserting the time buffers in strategic places in a time schedule, the algorithm provides protection against those main anticipated delays. The presented algorithm comprises two integrated components, a scheduling component responsible for producing a basic Linear Scheduling Method (LSM) schedule with deterministic activity durations, and a buffer component that handles fuzzy buffers sizing and insertion. The presented algorithm offers four different buffer insertion techniques covering different cases of interrelations between successive activities. The algorithm is implemented in a spreadsheet application, which automates calculations, yet allows users to fine tune the algorithm to fit the project at hand. With a focuses on highway construction projects as an example of repetitive construction projects, this paper accounts for sources of uncertainty such as weather, site conditions, change orders and equipment related delays. A hypothetical case is studied and explained to further demonstrate how the proposed algorithm works.

Aug 1, 2013

By Alvarez A. R, Garcia H. l

A fuzzy expert system, DIME, has been developed, under Matlab v 5.1. to assess the coal and gas outburst risk in underground mining. Expert systems and fuzzy logic are powerful tools to manage information represented by linguistic statements,

Jan 1, 1998

By J. N. Rivera

El objetivo del texto busca establecer una distribución más equitativa de los bonos mineros a través de un análisis de los factores influenciables en la explotación. El estudio describe un análisis detallado de los costos y eficiencias de una mina particular,diferenciándolos de los costos y constantes de un labor de corte-relleno, para asi determinar un sistema de bonos que tenga por base promedios pesados obtenidos del laboreo.

Nov 20, 1967

By Flavio Rojos-Tapia, Oscar Pereira-Cerda, Samuel Sánchez-Pino, Samuel Sánchez-Baquedano

"Pneumatic flotation was introduced to the Chilean Copper Mining Industry in 1993 by Ingeniería de Minerales S.A. (IDM). The technology is based on the designs of Dr. Rainer Imhof from Germany, who is the designer of several different types of pneumatic flotation cells, already sold through his Company Maelgwyn Mineral Service Limited (MMH). The company is represented by Ingenieria de Minerales S.A. (IDM) in South America.Pneumatic flotation, has been used in tough industrial applications .It has been successfully used for metallic ores such as copper sulphide and oxide minerals, copper slag, silica and silicates from iron magnetic preconcentrate (reverse flotation) and gold. It has also provided promising results when applied to molybdenum flotation. The latest applications, with ultrafine molybdenum particles in operating plants, is showing the V and G Cell (end model designed) as a real technological alternative to conventional flotation., The G Cell is an extremely high speed flotation machine with high selectivity which introduces the possibility of producing a final molybdenum concentrate with only one stage of cleaning. This is a completely new development in molybdenum flotation in the industrial circuit which has the potential to dramatically reduce the circulating load in the cleaning circuit. As a consequence the capital costs of future Molybdenum plants may also be reduced. The suitability of the G Cell will have to be determined on a case by case basis but it provides the metallurgist with an alternate flowsheet for consideration.The good performance of the G Cell can be explained by the high gas hold-up and very effective micro-turbulence which helps improve the attachment of solid particles to the bubbles. This technology may change our traditional concept of residence time in flotation. Additionally, the rotation phenomena introduced in the vessel of the G Cell ,creates radial separation forces which are critical to achieving a more rapid separation of the target minerals from the tailing. This results in a much reduced residence time requirement in the flotation machine. Some benefits associated with the use of the new G Cell are: less energy consumption, less maintenance costs, simple and reliable circuit to operate and a small area required for installing the circuits.As a result of the industrial experience in the Chile, the pneumatic flotation type G Cell can be regarded as a technology which must be considered as a replacement technology for the rougher and cleaner stages for fine particle flotation."

Jan 1, 2008

By AIME AIME

MOST recently elected to the limited group of Honorary Members in the A.I.M.E. is the distinguished Australian metallurgist, Guillaume Daniel Delprat. His citation reads: "in recognition of his distinguished achievement as metallurgist, engineer, and administrator in the production of ferrous and nonferrous metals," Mr. Delprat's ability and experience in both the ferrous and nonferrous fields at once distinguishes him from most of his professional brothers. Mr. Delprat's nativity was neither Australian nor English, for he was born in Delft, Holland, in 1856, and educated in Amsterdam. At the age of 22 he went to Spain, as metallurgist for the Tharsis Sulphur and Copper Co., Ltd. Afterwards he spent some time with the Bede Metal and Chemical Co., which had mines in both Spain and Norway, and of which company he became general manager. Other positions of responsibility held by Mr. Delprat before he went to Australia included the managing directorship of the Cordova Exploration Co., with properties in Spain and Canada; of the Rincon Silver-Lead Mining Co., in Spain; and of the Deloro Gold Mines, in Canada.

Jan 1, 1936

In the last 30 years numerous mining plants have been developed in North America but only a handful of these have required freezing the area where the shaft was sunk. The most recent mine shaft to be sunk using this technique is located on an island off the coast of Louisiana. The project required the input and skills of numerous people in several companies, including the owner, engineers and contractors. The Cote Blanche installation is one of several mines in the area which extract salt from a dome which extends under the Gulf of Mexico. The geology of this area is, however, markedly different from others in the region because there is approximately 460 ft of water logged soil above the salt dome. Because it is not possible to sink a shaft in ground that is this soft, the overburden where the shaft is located must be frozen before excavation can take place. The Cote Blanche mine is a producing facility which was built in 1958 by the Carey Salt Company. The original facility included a 14 ft diameter production shaft and a 7 ft-8 in diameter service/ventilation/escape shaft. This system was installed by The Cementation Company. In 1996 the owner decided to improve both the mine ventilation and production hoisting system by installing a third shaft. This shaft would be designed to extract 650 tons per hour from a depth of 1600 ft and provide 500,000 cfm of ventilation to the mine at a maxium design pressure of 4 in WG. These parameters resulted in a requirement for a 16 ft finished inside diameter concrete lined shaft and a headframe designed as a pressure bulkhead. Because the mine would operate from one level only, the most efficient hoisting system for the application was determined to be a ground mounted koepe running on rope guides. With these criteria fixed Cote Blanche embarked on a program which would see construction start in June 1998 with the first salt produced in February 2001 at a cost of $US18M. The major players in the design and construction were G.L. Tiley & Associates Ltd., BLM Bharti Engineering, Freezewall Inc., Phillips Mining, Geotechnical and Grouting Inc., Don Hart Consulting and Dynatec International.

May 1, 2002

Gaby Copper Mining?s Gabriela Mistral property is located in the Antofagasta region of northern Chile, at an altitude of 2,660 m (8,727 ft) above sea level. The reserve contains an estimated 562 Mt (620 million st) of oxide ore with an average grade of 0.41 percent total copper. The mine went into production in 2008. Gaby Copper faced the problem of having no reliable way to measure the solids level. This is a challenge that exists throughout the mining industry, where dust in the air and accumulation of solids on a sensor make accurate measurements difficult in areas such as transfer chutes, the rock box underneath crushers, silos and anywhere else that information is needed on the level of solids. The next-generation technology in the Sitrans LR560 radar from Siemens addresses this challenge. With a frequency of 78 GHz ? higher than previous generations of radar ? it provides a more robust signal for measuring in areas where there are high levels of dust accumulation. The Sitrans LR560 provides a signal beam angle of four degrees, significantly narrower than any other product on the market can offer.

Jan 1, 2014

THIS article describes the origin and details of a hydraulically operated switch to control the operation of an automatic underground pumping system. This system was installed in December, 1939, on the 2,350-foot level at No. 5 shaft of the Buffalo Ankerite mine. The pumping unit consists of an 8-stage centrifugal pump direct-connected to a 150 h .p., 2,200 volt motor. Pumping capacity is 200 gallons per minute under a 1,315-foot head and with a flooded suction. The control consists of a 200 amp., 2,200 volt oil-immersed starter with thermal overload protection, thermal protection on the pump, and a flow switch that is bypassed for 30 seconds after the pump starts. The 30-second time lag is operated by a relay mounted on the panel. There is a swing check valve in the discharge line of the pump which originally operated the flow switch by means of a connected outside lever which closed the switch as the check valve opened.

Jan 1, 1945