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Кафедра прикладных компетенций в области цифровых технологий
О центре
Cкорость научно-технологического прогресса и исчезновение определенных видов деятельности, связанное с проникновением автоматизации во все сферы производственных и управленческих процессов, являются факторами возможного роста для предприятий будущего. Цифровая интеграция, объединяющая научные направления, кадры, процессы, пользователей и данные, будет создавать условия для научно-технических достижений и прорывов, обеспечивая научно-экономические сдвиги в смежных отраслях и, прежде всего, на глобальном минерально-сырьевом рынке. В этой связи в 2018 году с целью обучения, исследований и разработок в области цифровых технологий для предприятий минерально-сырьевого и топливно-энергетического комплексов в Горном университете создан «Образовательный центр цифровых технологий».
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Направления научных исследований
Данное направление предполагает рассмотрение интеллектуальных технологий управления электроэнергетическими системами, включая передачу электрической энергии, управление спросом на электрическую энергию, цифровые двойники объектов электроэнергетики, цифровые информационные модели электротехнических систем.
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В рамках данного направления ведется разработка новых методов мониторинга и управления на основе цифровых и информационных технологий, создание информационных систем для решения задач горной отрасли.
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Данное направление нацелено на развитие и популяризацию инженерного образования, повышение цифровых компетенций сотрудников и обучающихся, а также реализацию программ дополнительного профессионального образования для представителей компаний ТЭК и МСК.
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Данное направление предполагает исследование и обоснование комплексных показателей эффективности генерации, транспорта и потребления энергии при снабжении от традиционных и возобновляемых источников энергии с учетом влияния глобальных вызовов и вариации внешних факторов.
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В рамках данного направления проводятся исследования, направленные на повышение эффективности оборудования и технологических процессов добычи, переработки и транспортировки полезных ископаемых.
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Проекты
Научные публикации
publications

About increasing informativity of diagnostic system of asynchronous electric motor by extracting additional information from values of consumed current parameter

Дата публикации: 2018-05-22
Журнал: Journal of Physics: Conference Series
Авторы: Zhukovskiy, Y, Korolev, N, Koteleva, N.
ISSN:17426596

This article is devoted to expanding the possibilities of assessing the technical state of the current consumption of asynchronous electric drives, as well as increasing the information capacity of diagnostic methods, in conditions of limited access to equipment and incompleteness of information. The method of spectral analysis of the electric drive current can be supplemented by an analysis of the components of the current of the Park's vector. The research of the hodograph evolution in the moment of appearance and development of defects was carried out using the example of current asymmetry in the phases of an induction motor. The result of the study is the new diagnostic parameters of the asynchronous electric drive. During the research, it was proved that the proposed diagnostic parameters allow determining the type and level of the defect. At the same time, there is no need to stop the equipment and taky it out of service for repair. Modern digital control and monitoring systems can use the proposed parameters based on the stator current of an electrical machine to improve the accuracy and reliability of obtaining diagnostic patterns and predicting their changes in order to improve the equipment maintenance systems. This approach can also be used in systems and objects where there are significant parasitic vibrations and unsteady loads. The extraction of useful information can be carried out in electric drive systems in the structure of which there is a power electric converter.
publications

AC motor diagnostics system based on complex parametric analysis

Дата публикации: 2017-03-01
Журнал: IOP Conference Series: Materials Science and Engineering
Авторы: Korolev, N.A, Solovev, S.V.
ISSN:1757899X

The article deals with the principle of evaluation of technical condition, based on a comprehensive analysis of the motor parameters which is a main unit in mechanical engineering. Diagnostics system and residential life assessment of electromechanical equipment is presented based on the AC engine and algorithms of its work. The important challenge of diagnostics remains the well-timed faults detection and maintenance and repair organization. The solution of such challenge remains accuracy and reliability of diagnostic systems.
publications

Identification of the technical condition of induction motor groups by the total energy flow

Ключевые слова:Classification algorithm | Current harmonic distortion factor | Induction electric motor | Simulation model | The coefficient of electromagnetic momentum ripple
Дата публикации: 2021-10-01
Журнал: Energies
Авторы: Koteleva, N.I, Korolev, N.A, Zhukovskiy, Y.L.
ISSN:19961073

Q2

(Scimago)

The paper discusses the method of identifying the technical condition of induction motors by classifying the energy data coming from the main common power bus. The work shows the simulation results of induction motor operation. The correlation between occurring defects and current diagrams is presented. The developed simulation model is demonstrated. The general algorithm for conducting experiments is described. Five different experiments to develop an algorithm for the classification are conducted: determination of the motors number in operation with different power; determination of the motors number in operation with equal power; determination of the mode and load of induction electric motor; determination of the fault and its magnitude with regard to operation and load of induction motor; determination of the fault and its magnitude with regard to operation and load of induction motor with regard to non-linear load in the flow. The article also presents an algorithm for preprocessing data to solve the classification problem. In addition, the classification results are shown and recommendations for testing and using the classification algorithm on a real object are made.
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Отзывы партнёров
"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
 
 
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