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Educational Center of Digital Technologies
About center
The speed of scientific and technological progress and the disappearance of certain activities associated with the penetration of automation into all areas of production and management processes are factors of possible growth for enterprises of the future. Digital integration, which integrates scientific directions, people, processes, users and data, will create the conditions for scientific and technological advances and breakthroughs, enabling scientific and economic shifts in related industries and, above all, in the global mineral market. In this regard, in 2018, for the purpose of training, research and development in the field of digital technologies for the enterprises of mineral and fuel and energy complexes, the "Educational Center of Digital Technologies" was established at the Mining University.
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Directions of scientific research
This direction implies the consideration of intellectual technologies of electric power systems management, including electric power transmission, electric power demand management, digital twins of electric power facilities, digital information models of electrical engineering systems.
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Within the framework of this direction, new methods of monitoring and management based on digital and information technologies are being developed, and information systems are being created to solve mining industry problems.
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This direction is aimed at the development and popularisation of engineering education, improvement of digital competencies of employees and students, as well as implementation of additional professional education programmes for representatives of fuel and energy complex companies.
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This direction implies research and substantiation of complex indicators of efficiency of energy generation, transport and consumption when supplied from traditional and renewable energy sources, taking into account the impact of global challenges and variation of external factors.
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Within the framework of this direction, research is carried out aimed at improving the efficiency of equipment and technological processes of mining, processing and transporting minerals.
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Scientific publications
publications

Technical vision system for analysing the mechanical characteristics of bulk materials

Date of publication: 2018-01-30
Journal: Journal of Physics: Conference Series
Authors: Boikov, A.V, Payor, V.A, Savelev, R.V.
ISSN:17426596

In this article actual topics concerned with mechanical properties of bulk materials, usage of computer vision and artificial neural networks in this research are discussed. The main principles of the system for analysis of bulk materials mechanical characteristics are described. Bulk material outflow behaviour with predefined parameters (particles shapes and radius, coefficients of friction, etc.) was modelled. The outflow was modelled from the calibrated conical funnel. Obtained dependencies between mechanical characteristics and pile geometrical properties are represented as diagrams and graphs.

Production Process Data as a Tool for Digital Transformation of Metallurgical Companies

Keywords:BigData | Correlation coefficient | Data analysis | Data preprocessing | Digitalisation | Production statistics
Date of publication: 2022-01-01
Journal: Lecture Notes in Networks and Systems
Authors: Stoianova, A, Vasilyeva, N.
ISSN:23673389

Q4

(Scimago)

Big Data analysis is becoming an everyday task for companies all over the world, including Russian companies. Due to advances in technology and the reduction in the cost of storage systems, companies can now collect and store large volumes of heterogeneous data. The important step of extracting knowledge and value from such data is a challenge that will eventually be met by all companies seeking to maintain their competitiveness and place in the market. However, companies face several challenges when it comes to collecting, pre-processing, and integrating data into cohesive data sets designed to deliver analytics. In this article, the above problems and possible solutions are illustrated using the example of cleaning, integration, and normalization of data obtained in the measurement of indicators for the Vanyukov melting furnace process. The article considers an approach to the study of metallurgical processes using the analysis of large operational control data sets. Standard methods of processing the data sets of operational process control are used. The correlation analysis of the main process parameters is carried out. The results are interpreted for their further practical application.
publications

DEM calibration approach: Orthogonal experiment

Date of publication: 2019-05-04
Journal: Journal of Physics: Conference Series
Authors: Boikov, A.V, Savelev, R.V, Payor, V.A, Vasileva, N.V.
ISSN:17426596

The research considers conducting orthogonal experiment (OT) as one of the stages in developing a new discrete element method (DEM) parameters calibration approach. The measured responses in experiment are the parameters obtained by DEM animation processing using machine vision system (MVS). The variable factors in experiment are DEM parameters. A brief overview of an existing calibration approaches given in the article. The choice of OT as a design of experiment tool among other mathematical tools discussed. Experiments conducted using specially developed rig where bulk material's flow captured as DEM animation. DEM animation converted to video and then processed using MVS that allow register the values of such parameters as angle of repose or expiration time (measured responses). The results of the OT show that it is possible to identify four measured responses with the most valuable correlation coefficient. DEM parameters with the biggest influence on the measured responses identified for each of the obtained regression. Obtained results are useful in learning or iterative algorithms development for DEM parameters calibration.
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Partner reviews
"Together with the Educational Center of Digital Technologies at St. Petersburg Mining University, we have been collaborating for several years to shape fundamental and applied challenges and ideas for the digitalisation of the mining industry."
"We are very glad to be part of the process that the Educational Center of Digital Technologies at St. Petersburg Mining University is engaged in. We are confident that this centre can become an assembly point for all those new solutions that will bring the mining industry to a new level."
The Committee for the Fuel and Energy Complex of the Leningrad Region expresses its gratitude to you for your support in holding the Festival and organising an informative exposition of the enterprise aimed at attracting the young generation to the fuel and energy complex profession.
Thanks to your efforts, we will be able to further educate young people full of strength and aspirations for knowledge and creativity in the field of energy saving.
We hope for further fruitful co-operation in the field of energy saving.
On behalf of the Ministry of Energy of Russia, we would like to express our gratitude to the WeWatt team of young researchers for the great and necessary work for the industry, done under your leadership on a proactive and pro bono basis.
The results of this study will serve as a basis for further work in this area and will be useful to coal companies in carrying out digital transformation of production facilities, contributing to the effective and successful achievement of the goal.
Institute for Problems of Integrated Subsoil Development, Dmitry Klebanov
Leonid Zhukov, Director of SITECH Division of Zeppelin Rusland Ltd.
Committee for Fuel and Energy Complex, Chairman of the Committee Y.V. Andreev
Ministry of Energy of the Russian Federation
 
 
reviews

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