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have a method for the breaking of obstacles. Mining robotics most probably will be developed step by step in the following stages:

1)Telemanipulators for mechanization of manual works.

2)Operator alternatives remote control and automatic control of telemanipulator under direct visibility, then control from surface is obtained.

3)Concerted actions of a few robots in some technologies.

4)Control systems of robots are connected by mine-wide information network.

5)Computer Aided Design (CAD) and Computer Aided Mining (CAM) are put into practice for mine planning, monitoring, and control of mining machines in real-time.

For intelligent mining, the robots will change positions of working heads, movement in space, step and speed for both extraction and roof support depending on mining conditions. These will make possible to avoid some geological hazards, avoid dangerous rock pressure manifestations, stabilize a quality of mining and increase the utilization of machines.

XIII. Prepare and ask your groupmate questions about: a) robot functions; b) adaptivity of robotic systems; c) the aims of mining robots.

XIV. Give the brief description of: a) a remotely-controlled robots; b) multifunctional technological robots; c) a mine rescue robot; d) the steps of mining robots development; e) robots for intelligent mining.

XV. Read and translate the text given below. Using it prepare short reports on the following topics: a) robotics-based mining in thin coal seams; b) robotics-based technology for thick steep seams; c) technological robots working tools; d) haulage by transport robots.

ROBOTICS-BASED MINING

Certain mining technologies cannot be realized without robotics. Robotics-based mining was developed for winning thin steep coal seams that were inaccessible for miners. At first, a shearer extracts

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coal from belt road to an open air road. Then one drops the coal to a belt road. After that a manipulator advances an inflatable balloon support to the face.

The analysis of the cinematic interaction between the robot and the balloon showed it must have masse 290 kg and the manipulator a length of 1,1 m. The balloon is connected via robot joints and to a pneumatic system. A balloon moves to face similar to the motion of a pendulum. When it is at the face, the robot gives some air to set it to load.

The following robotics-based technology was developed to mine coal from thick steep seams. At first, the line of arches with a meshwire lagging is mounted under the artificial roof on the floor of a slice drift. A winning machine moves from a coal chute to a ventilation raise. Coal is transported by conveyor inside the arch support powered support moves after the machine and supports some upper arches. Then a regular arch is lowered by manipulator on the floor of slice drift. This technology is suitable for seam thickness more than 8 meters with angles of dip 45–90Ä. During a dynamic simulation using Petri nets, it was determined the lowering up 20% sections in nonautomatic mode of the operation reduces the total output by 15% if a labour intensity is 20 men-minute for a single arch.

Technological robots can have working tools with the cinematic structure known as SCARA that is popular for machine-building robotics. This allows a working head to be constructed for a selective heading machine. Owing to a rotary movement between manipulator links, a working tool has a large service space attached to a compact working head.

In general, the electro hydraulic control of a powered support during longwall mining requires a separate control system for every support unit with their unreliable connections along a face. Instead of this, a robot can move behind a shearer and then switch the hydraulic distributor of unit by using an infrared transmitter. The distance between shearer and shifted support unit can be changed.

This type of robotics forms the basis for intelligent mining. These stages of robotics integration for future mining can be demonstrated by means of an example. Usually, a rail train with many winches is used for the haulage of loads to faces.

Haulage by transport robot enables to remove hard manual re-

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loading on a way to faces. Then any loads are transported in good time according to current orders from face-miners. As the simulation by Petri nets showed, a single robot is able to service up 4 faces on a distance up 500m, if the orders from face miners are received in every hour. After that a current calculation of goods traffic is introduced. Next, the optimization of underground traffic in real-time is realized. Finally, this system is connected with computer system of material supply and a total control of mine.

In future, robotics-based mining will be based on a concerted action of distributed equipment during mining, work in dangerous places, rock-breaking by local nuclear explosion, laser control, high pressure jets and rock treatment by glue or foam. An underground mine with robots can be filled by natural methane to prevent fire-damp explosions and reduce the cost of ventilation, driving, and explosionproof electrical equipment.

XVI. Make up dialogues on the following topics: a) deteriorating mining conditions and the necessity of mining robotics; b) the history of mining robots appearance; c) aims of mining robotics; d) types of mining robotisation; e) comparison of a miner and robot functions.

XVII. Translate one part of the text given below in writing.

ADVANCED TECHNOLOGIES

AND LOADING SHOVEL DESIGN

I. The use of computer-aided design systems in shovel design has been in place for many years. However, recent advances in computer capability and improved software programs and graphics are making computers even more useful.

Loading shovels are at the heart of most surface mine production. As truck sizes have increased, shovel manufacturers have matched them with larger shoves. Further increases in shovel size may be in order if trucks in the 270-t (300-st) range find acceptance at the largest surface mines.

However, larger shovels are not currently the primary focus of shovel design engineers. Competition and user pressure are combining

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to keep their work directed toward improved shovel productivity and efficiency. Computer design technology and advanced electronics play an increasingly prominent role in this work.

“Improved diagnostic capability, system monitoring, vibration analysis and above all increased user friendliness in machine control systems are being pursued by most manufacturers working in our industry today,” observes Stuart R. Cotterill, director of marketing for Harmschfeger Corp.

The use of computer-aided design (CAD) systems in shovel design has, been in place for many years. However, recent advances in computer capability and improved software programs and graphics are making computers even more useful.

Among other impacts, computers allow a company to bring a new shovel to the field much more quickly. Bob Griffiths, a Caterpillar design engineer, reports that “We started with the 5130 and had the machine in iron in one-a-half to two years. About halfway through that program, we started on the 5230, and a little over a year after that, that machine was in iron. It was introduced in the fall of 1994”.

“In the past, these programs might have taken three years. The biggest gains have been in turnaround times, faster computers and working concurrently in the engineering and manufacturing process.”

II. All shovel manufacturers emphasize easy access to machine service points. Walk-in access to engine and pump compartments is a design standard, as are automatic central lubrication systems. Cabs specifically designed for operator comfort and operating efficiency are also standard.

Most of the hydraulic loading shovels discussed in this article can be equipped for backhoe loading, or “mass excavation”. Such use is gaining acceptance in some applications. “We are seeing that large contract miners may be more inclined toward the mass excavator (loading backhoe),” says Paul Ludwigsen, a Caterpillar design engineer.

“Especially the Australians, who are looking at these machines for work in the western gold fields when they have a fairly homogenous ore body. They can design their bench height to take advantage of the mass excavator’s loading ability. They are also using them in the coal fields in the Bowen Basin and the Hunter Valley to chase rolling and dipping seams of coal to take away the partings. They have

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really worked at setting up a job to take advantage of the capability of an excavator where you can get your swing down from 20Ä to 25Ä, while for shovels, swings are usually in the range of 45Ä to 90Ä.

CAD and other more recently designed tools are contributing to the optimization of all major shovel components. “Forty years ago mining shovels were designed by conventional means, which included generous overdesign and factors of safety to accommodate indeterminacy and unknowns,” explains B-E design engineer, B. M. Lang. “In today’s competitive world, excess “fat” has been taken out of designs.”

“Designers now rely heavily on finite element analysis (FEA) as the primary design tool to determine stress and suitability, especially in more complex areas. FEA has also become a primary tool for analysis of field problem areas,” Lang says. “Before-and-after computerized stress levels can be correlated to elapsed time when a problem occurs, to project increased component life”.

“The way computers are used in the design of mining machinery has evolved markedly in the last four years. Where we previously ran CAD programs and FEA on mainframes, we are now on the third generation of engineering workstations. The new hardware and software permit finely meshed solid element FEA models to be solved quickly,” says Lang. “Where previous! у a plate element model was used to recover stresses adjacent to critical welds, we now model the welds themselves with solid elements”.

XVIII. Ask in oral as many questions as you can on the translated part from the text given above. Your partner is to check the correctness of your questions.

XIX. Read the first and the second paragraphs of the text given above. Find the answers to the following questions. 1) What machines are mostly necessary for surface mining? 2) Why do shovel manufacturers produce shovels of larger size? 3) Why is it profitable to use larger and larger trucks and shovels at the surface mines? 4) Is the problem of larger shovels the primary focus of shovel design engineers? 5) What is their work directed towards?

XX. Read the text given above up to the end.

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XXI. Organize a kind of a press-conference. Four students speak on the name of design engineers Lang, Ludwigsen, Griffiths, Cotterill. The rest of the students present shovel users and ask design engineers questions about: a) the period CAD is being used in shovel design; b) what makes computers more useful; c) easiness of maintenance of loading shovels; d) cabs design; e) possibility of backhoe loading.

XXII. Make up an oral abstract of the given above text.

XXIII. Read the first part “Abstract” of the below text. Retell it.

COMPUTER TECHNOLOGY FOR ESTIMATION AND FORECASTING OF ENVIRONMENTAL CONDITIONS IN MINING REGION

I. Abstract.

Problems of the creation of an automated cartographic system for environmental condition estimation and forecasting in mining region are discussed in this paper. The Geographic Information System (GIS) ARC/INFO is offered as the platform for such a system.

A breadboard model of the system was tested on the example of Kemerovo province (Kuznetsk coal basin), the most ecologically impacted mining region of Russia.

As a result parameters of territorial distribution of integrated adverse environmental impact of the industrial enterprises are reviewed. Administrative regions of Kemerovo province were rated according to a degree of environmental pollution. Further, specific weight of various industries in pollution of region is determined.

II. Introduction.

In most of the mining regions of Russia are a territorial set of mining enterprises and consumers of mineral raw material, namely: metallurgical and chemical factories, and enterprises of power and construction industries.

These regions are characterized by the multiple and large-scale effect of industry on all spheres of the environment: atmosphere, biosphere, hydrosphere and lithosphere.

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More than 900 industrial enterprises of a fuel industry (coal and power engineering) ferrous and non-ferrous metallurgy, oil industry and others exert an adverse environmental impact in Kemerovo province.

The level of influence of the types of industry on various environmental spheres is different. About 90 per cent of all discharges into the atmosphere in the Kuznetsk Basin are made by enterprises of ferrous and non-ferrous metallurgy. Sources of industrial effect on the lithosphere are the enterprises and projects dealing with extraction and processing of minerals. Most of them are related to the coal industry: 102 underground mines, 25 open cut mines and 16 coal preparation plants are located in the basin. Pollution of underground and surface waters is caused equally by enterprises of all industries. Practically all waste waters (more than 300 million m per year) are dumped to natural reservoirs without treatment.

Software for estimation and forecasting of the state of the environment should be a component of an ecological monitoring system. This system should be based on supervisory data describing natural objects and sources of industrial effect. It is necessary to provide data acquisition for large sources of pollution in order to receive a full description of the environment slate and create appropriate conditions for the decision making on a regional level (examination, forecasting and management).

Monitoring systems of this type, meeting general requirements and corresponding to mining region features are non existent.

Effective nature conservation during exploration of mineral deposits is impossible without the creation of permanently working ecological monitoring systems in the mining region. Creation of a theoretical basis for these systems is one of the main environmental management problems of mining science today.

III. Breadboard model of the system for estimation and forecasting of environmental condition in mining region.

A system of estimation and forecasting of environmental conditions in a mining region should be based on adequate computer/information technology. As ecological monitoring is connected with the analysis of spatial objects and conditions, an information system should provide input, storage, processing and representation of the geographically linked information.

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The geographical information systems (GIS) are the most appropriate software tools for the decision of the specified tasks, including database management with visualization and analysis of the spatial data.

The database should contain the pollution parameter values of various natural spheres: and data describing industrial enterprises of region. These are conditions of successful solutions of main environmental tasks: restoring of space-time fields of ecological factors, revealing of man sources of pollution and forecasting of territory pollution.

The breadboard modeÆ of this system was used mainly, for checking of data management and representation technology, in addition for testing user cartographic interface. Flexibility of developed software is provided-far the subsequent creation of the working version of system. Change of data structure, connection of new application, modification of view (image) and contents of screen maps and printed documents are available.

The Breadboard model of system assumes the following reservations:

1.Available tools: managing data of the enterprises ecological passports, relevant to atmosphere pollution; restoring, analysis and graphic representation of spatial fields of the atmospheric ecological factors based on data of point measurement; managing screen map, choosing of scale and mode of displaying.

2.The database structure describes the content of the tables of the enterprise ecological passport, data for atmosphere pollution forecasting and estimation of maximum permissible discharge, and general information on the enterprise.

3.Topographical maps of scale 1:500 000 (covering area as a whole) and maps of larger scale (1:50 000) for some of the most important industrial regions were used.

GIS ARC/INFO (version for PC) was used as a software tool for design and implementation of the system.

XXIV. Read the second part “Introduction” of the above text. Using the sentences from it prove the statements. 1) About 90 per cent atmospheric pollution in Kemerovo region are made by ferrous and non-ferrous industry. 2) Permanently working ecological

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monitoring system is necessary in the mining region. 3) Mining regions in Russia are accompanied by different industrial enterprises. 4) Monitoring system of this kind doesn’t exist. 5) Mining regions are characterized by multiple and large-scale effect of industry. 6) Practically all waste waters are dumped to natural reservoirs without treatment. 7) Adequate software should be a component of a monitoring system. 8) Extractive and processing industry affects the lithosphere. 9) A large amount of data is necessary to receive a full description of the environment state. 10) More than 900 industrial enterprises exert an adverse environmental impact in Kemerovo province.

XXV. Read the above text up to the end.

XXVI. Give the description of: a) technology and information the system is based on; b) application of the breadboard model; c) reservation of the breadboard model; d) CIS; e) database.

UNIT XIII

APPLICATION OF AI AND ROBOTICS TO MINING

I. Study the given below texts at home. Compare the state of automation and computerization of mines in Russia and Canada.

APPLICATION OF ARTIFICIAL INTELLIGENCE

AND ROBOTICS TO MINING

I. Introduction.

In recent years, Canadian research and Industrial organizations like the National Research Council (NRC) and Canada Centre for Mineral and Energy Technology (CANMET), a Federal Government Division have investigated how Artificial Intelligence (Al) techniques and robotics technology can be applied to problems in mining. The application of high technology is one of the most effective methods for improving productivity and ensuring sale working conditions in a hazardous occupation such as mining. The idea of totally automating the extraction process, although not new, was not believed to be practical. Now, the fully automated and unmanned mine Ts probably only a decade away. Automation of coal mines began many years ago

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with the Introduction of mechanical haulage devices, conveyors, and shearers on the coalface. In the mid-1950s the drive to mechanize underground operations particularly those associated with the coalface, was accelerated, and by the mid-1970s the process was virtually completed. In parallel with this mechanization, attempts were made to automate coal transport systems and, to a lesser degree, monitor coalface operations. While some success was achieved with the former, little progress was achieved with the attempts to monitor coalface operations. These early failures can be attributed to (1) the methods in which monitored information was presented, (2) technical limitations of the equipment then available and (3) lack of communication technology to coiled transmit, process and display data.

The locus of this paper is on the applications of robotics to mining. The evolution of automated systems into robotic systems has taken place to two stages, as far as industrial applications are concerned.

The first stage consisted of robotic systems distinguished by their versatility and flexibility; a large number of repetitive tasks were programmed into the robots. Most of the robots in use today fall into this category.

The second stage of development began recently with the interactive robot, which interacts with its physical environment. This robot can be thought of as an “AT robot” in the sense that the interactions are due to the intelligence built into it. In this paper, we refer to robotics in both senses and include processes associated with the robots. There are three main aspects of mining in which robots can be used: exploration, production and aiding humans with difficult or dangerous tasks. Using robots during exploration operations allows work to be carried out in hostile environments-for example, under water, in an underground mine, in radioactive areas or in high temperature/humidity environments.

This paper describes the mining applications of robotics, and then explores the possible use of teleoperation in mining, partly for exploitation, but mainly for the maintenance of automated systems in mines. The problems of determining how much automation is really needed for the Integration of advanced technology to mining are then discussed, and various approaches are described.

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