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Научные публикации

The control method concept of the bulk material behavior in the pelletizing drum for improving the results of DEM-modeling

Ключевые слова: A probe | Cast iron production | DEM-modeling | Digital twin | Drum pelletizers | Pelletizing automation | Track recovery | Wear pattern | Wear rate
Дата публикации: 2019-01-01
Журнал: CIS Iron and Steel Review
ISSN: 24141089
Авторы: Boikov, A.V, Savelev, R.V, Payor, V.A, Erokhina, O.O.

Q1

(Scimago)

One of the problems of the use of drum pelletizers in metallurgy is the lining wear, as well as the economic costs associated with it, including increased energy costs during operation and the need to periodically stop the units and then replace the lining. Most significantly the trajectory of particle motion affects the lining wear profile and wear intensity. It is assumed that during the implementation of the technological process, a monodisperse occurs, which has the greatest effect on the wear profile. In addition, the lining wear is influenced by the impact of particles at an acute angle, with a maximum impact caused by a collision at an angle of 39°18′. At present there are no universal solutions for determining the degree of lining wear in real time with a corresponding adjustment of the pelletizing process parameters. Creating a system for monitoring the lining wear is necessary for timely repair and maintenance of equipment to prevent an emergency situation, as well as increase the service life of the aggregates. This article proposes a concept of a method that allows to evaluate the trajectory of the charge during the technological process according to the coordinates of the movement and acceleration of the probe in the unit during the implementation of the technological process. The digitization and analysis of data obtained from the probe will allow to assess the integrity of the lining surface, the degree of lining wear and places with increased wear rate in real time with the possibility of adjusting technological processes to increase the lining service life. The obtained data will allow to clarify the computer model of the process by assessing the behavior of the charge in the unit and create a reserve for the further implementation of digital twin equipment.
publications

Evaluation of bulk material behavior control method in technological units using dem. Part 2

Ключевые слова: Bulk materials | Classification of motion modes | DEM-modeling | LSTM | Neural networks | Pelletizing drums | RNN
Дата публикации: 2020-01-01
Журнал: CIS Iron and Steel Review
ISSN: 24141089
Авторы: Boikov, A.V, Savelev, R.V, Payor, V.A, Potapov, A.V.

Q1

(Scimago)

The research is dedicated to the development of special devices (capsules) that can be used to control the mining ore behavior in the technological unit in order to increase processes efficiency. In the first part of the article, the choice of the discrete element method for gen-erating various particle trajectories in the unit (drum pelletizer) was substantiated. This part describes the specific technologies that were used to recognize the pelletizing mode. In par-ticular, conversation of paths to sensor readings is implemented using the Matlab Sensor Fusion and Tracking Toolbox. The obtained readings were processed using two neural network classifiers (DNN and LSTM). As a result, stable models for recognizing the pelletizing modes of the unit were obtained. LSTM recognition accuracy is greater than DNN. The developed approach can be used to recognize the operating modes of other technological units. In addition, data on particles trajectories can be used to improve DEM models of technological processes. Future work consists of the capsule physical implementation and testing the recognition algorithm on a real unit.

Evaluation of bulk material behavior control method in technological units using dem. Part 1

Ключевые слова: Bulk materials | Classification of motion modes | DEM-modeling | Neural networks | Pelletizing drums
Дата публикации: 2020-01-01
Журнал: CIS Iron and Steel Review
ISSN: 24141089
Авторы: Boikov, A.V, Savelyev, R.V, Payor, V.A, Erokhina, O.O.

Q1

(Scimago)

Nowadays pelletizing drums are widely used in the steel industry. These units are characterized by high endurance and low cost of maintenance. However, use and control of these units in the process of coarsening have a number of issues. For most of the cases pelletizing drums are “black box” and control accuracy can not be estimated exactly. It is explained by low existing theoretical basis of this production process. Particularly it is tied up with the variability of the bulk materials (charges) parameters supplied to the unit. Overcome of this issues can be reached with development of intelligent control systems for drum pelletizing machines. Main requirement for such systems is possibility to level or consider the effect of charges properties variability in control. However, it is necessary to study the behavior of bulk materials inside the units. Visual assessment of pelletization does not allow to evaluate the ongoing physical processes. Development of mathematical and numerical models can help studying the process and take a lot of parameters into account including charges properties and even interaction with water. But the adequacy of the resulting models also has to be clarified using physical devices to record or capture bulk materials behavior inside the units. This research proposes a DEM simulation test of the concept for bulk material behavior control through the recognition of the mixture movement fragments using special capsules. This part is dedicated to the simulation model set up and extracting the particles trajectories for further processing.
publications

The influence of technological changes in energy efficiency on the infrastructure deterioration in the energy sector

Ключевые слова: Digital technologies | Global challenges | Infrastructure deterioration | Sustainable development | Sustainable energy | Technological changes
Дата публикации: 2021-11-01
Журнал: Energy Reports
ISSN: 23524847
Авторы: Shabalov, M.Y, Zhukovskiy, Y.L, Buldysko, A.D, Gil, B, Starshaia, V.V.

Q1

(Scimago)

The energy and its entire related infrastructure are the main drivers for a economic development and for ensuring a good level of employment. As part of a global study about international energy sector, we evaluate here the impact of technological changes on the state of the energy infrastructure. This study includes a detailed analysis of the global challenges facing the energy industry. We propose scenarios for the development of a modernized energy infrastructure with an assessment of the entire energy system. Our evaluation indicators are chosen in terms of the reliability of the energy infrastructure, of its quality, of the accidents that may happen and of the consequent environmental risks. This study is particularly adapted for forecasting the necessary measures (of technical nature, of governance kind) that have to be implemented to reduce the acceleration of the infrastructure deterioration rate. Our results reveal that the use of digital and information technologies has many positive impacts on the development and on the control of an efficient consumption of energy. In addition, our predictions, due to the further modernization of the energy sector, can contribute and help in the creation of preconditions that will be highly stimulating and profitable to the growth of investments in the energy infrastructure.
publications

Development of an algorithm for regulating the load schedule of educational institutions based on the forecast of electric consumption within the framework of application of the demand response

Ключевые слова: Big data | Demand response | Digital technologies | Energy efficiency | Energy saving | Internet of things | Machine learning
Дата публикации: 2021-12-01
Журнал: Sustainability (Switzerland)
ISSN: 20711050
Авторы: Zhukovskiy, Y.L, Kovalchuk, M.S, Batueva, D.E, Senchilo, N.D.

Q1

(Scimago)

There is a tendency to increase the use of demand response technology in the Russian Federation along with other developing countries, covering not only large industries, but also individual households and organizations. Reducing peak loads of electricity consumption and increasing energy efficient use of equipment in the power system is achieved by applying demand management technology based on modeling and predicting consumer behavior in an educational institution. The study proposes to consider the possibility of participating in the concept of demand management of educational institutions with a typical workload schedule of the work week. For the study, statistical data of open services and sources, Russian and foreign research on the use of digital and information technologies, analytical methods, methods of mathematical modeling, methods of analysis, and generalization of data and statistical methods of data processing are used. An algorithm for collecting and processing power consumption data and a load planning algorithm were developed, including all levels of interaction between devices. A comparison was made between the values of the maximum daily consumption before and after optimization, as well as the magnitude of the decrease in the maximum consumption after applying the genetic algorithm. The developed algorithm has the ability to scale, which will increase the effect of using the results of this study to more significant values. Load switching helps to reduce peak consumption charges, which often represent a significant portion of the electricity cost.
publications

Public-private partnership as a tool of sustainable development in the oil-refining sector: Russian case

Ключевые слова: Energy and resources policy | Investments | Oil-refining sector | Public policy | Public-pri-vate partnership (PPP) | Russia | Sustainable development | Synergetic effect
Дата публикации: 2021-01-01
Журнал: Sustainability (Switzerland)
ISSN: 20711050
Авторы: Filatova, I, Nikolaichuk, L, Zakaev, D, Ilin, I.

Q1

(Scimago)

Dramatic changes in the global energy market due to COVID-19 pandemic, the OPEC+ agreement, and increasing rates of green energy share in the world community have brought nega-tive effects on the oil sector. In the long term, oil will reduce its importance as an energy resource, but for many years, it will continue to play a significant role in the world of energy. The oil industry has huge potential in terms of technical expertise, management, and financial resources to reduce its greenhouse emissions and ensuring an affordable availability of predictable energy. However, nowadays this sector has lost investing attractiveness. It is an interdisciplinary problem with a so-lution at the intersection of different stakeholders’ interests. The article is a review one and devoted to the issue of the implementation a public-private partnership (PPP) as a key tool that allows the use of the state and the business’ available resources to achieve the sector’s sustainable development and investment attractiveness. Research and analysis of PPP were based on foreign and domestic literature, using classification and generalization methods, retrospective and critical analysis. This paper contains identified groups of drivers, constraints, and recommendations for further successful PPP implementation in the Russian case.
publications

The concept of digital twins for tech operator training simulator design for mining and processing industry

Ключевые слова: Digital twin | Dynamic modeling | Extended reality | Intelligent system | Mining and processing industry | Production safety | SCADA-system | Simulator | Training | Transformation
Дата публикации: 2020-01-01
Журнал: Eurasian Mining
ISSN: 24140120
Авторы: Beloglazov, I.I, Petrov, P.A, Bazhin, V.Y.

Q1

(Scimago)

According to the top-priority trends and challenges in the mineral sector, and as per the mining science strategy, it is highly critical to arrange enhanced control, prediction and safety of production objects and their functioning for the preservation of automation sustainability. Improved control of databases, regulatory bonds, management, logistics and principles of sustainable development in mining makes it possible to reduce technological deviations and accidents at large mining and processing plants. Most procedural violations and accidents in surface and underground mines occur because of the unskilled actions of process flow operators. Damage in this case can be considerable, especially as compared with the expenses connected with qualitative training and persistent development of personnel engaged with supervisory control and data acquisition for the efficient operation of SCADA-systems within the automation framework of mining and processing plants. Definition of digital systems and their interrelation with multilevel automated control can be incorrect. The review of new principles can awaken interest in the conceptual assessment of digitalization processes using such notions as: numerical models, simulator, and artificial intel-ligence. Often applied formulations and principles of a digital model are substituted without justification of functional connections. On the other hand, a digital system today can be assumed as robotic lines and other numerical models and smart technologies, for instance, machining sta-tions with numerical program control. It is necessary to define the practical significance of conceptual modifications and digital transformation regarding objects of the mineral sector, using Big Data; to understand how a digital twin can influence a changeable process situation; to provide prompt prediction; to eliminate an accident; and to preserve the physical balance in the whole production system. Such intelligent and flexible productions particularly need computer-based simulators and digital twins based on technologies of Industry 4.0–extended and virtual reality on the basis of digital twins. Digital twins allow maximal simulation of real-life activity of process flow operators. The skills acquired by personnel after such simulation training enable operators to master the optimized procedure for functioning in emergency situations in mineral mining and processing. This paper exemplifies the remote training and control of process flows, which is of concern in the current international situation.
publications

Flow modeling of high-viscosity fluids in pipeline infrastructure of oil and gas enterprises

Ключевые слова: ANSYS | Flow model | Heavy oil | High-viscosity oil | Oil field pipeline | Rheology
Дата публикации: 2021-12-01
Журнал: Egyptian Journal of Petroleum
ISSN: 20902468
Авторы: Beloglazov, I, Morenov, V, Leusheva, E.

Q1

(Scimago)

Today, the issues related to solving the problem of finding an effective distribution of oil flows through the system of oil pipelines in order to reduce the total energy consumption are relevant. The solution to this problem is connected with selection of rational pumping modes for various technological sections of oil pipelines using modern methods of mathematical programming or new techniques for improving the energy and transport characteristics of oil. Reducing energy consumption during pumping of crude through oil trunk pipelines can be achieved by various methods. Numerous investigations in this direction are mainly carried out to save energy on separate single-line pipelines. However, due to the development of the network of trunk oil pipelines in the world over the past decades, the issues of energy efficient management of oil flows throughout the entire oil pipeline system of oil and gas enterprises become urgent. This paper analyses parameters for pipeline transport of high-viscosity and heavy oils. The article proposes a method for assessing the rheological properties of oil for further planning of pumping taking into account the preservation of oil quality and an increase in energy and transport characteristics. The proposed solutions and tasks for predicting changes in the viscosity-temperature characteristics of the flow for blends of different oil types are especially relevant in the current conditions of an increase in the share of oil production with complex rheological characteristics. Results of the presented investigations may be used for planning the measures of efficient transportation of high-viscosity and heavy oils.
publications

Synthetic data generation for steel defect detection and classification using deep learning

Ключевые слова: Computer vision | Machine learning | Steel defect detection | Synthetic data
Дата публикации: 2021-07-01
Журнал: Symmetry
ISSN: 20738994
Авторы: Boikov, A, Payor, V, Savelev, R, Kolesnikov, A.

Q2

(Scimago)

The paper presents a methodology for training neural networks for vision tasks on synthe-sized data on the example of steel defect recognition in automated production control systems. The article describes the process of dataset procedural generation of steel slab defects with a symmetrical distribution. The results of training two neural networks Unet and Xception on a generated data grid and testing them on real data are presented. The performance of these neural networks was assessed using real data from the Severstal: Steel Defect Detection set. In both cases, the neural networks showed good results in the classification and segmentation of surface defects of steel workpieces in the image. Dice score on synthetic data reaches 0.62, and accuracy—0.81.
publications

Improving transportation efficiency belt conveyor with intermediate drive

Ключевые слова: Bet conveyor | Intermediate drive | Linear actuator | Partitions | Tension
Дата публикации: 2019-01-01
Журнал: Journal of Mining Institute
ISSN: 25419404
Авторы: Trufanova, I.S, Serzhan, S.L.

Q2

(Scimago)

Modern industry in the XXI century requires high-performance and fully automated technology. The best way to meet these requirements is the introduction of new progressive technologies in the process of transportation. One of the possible ways to increase productivity, as well as automate the process of transportation, is the transition from cyclic machines to continuous transport, namely to belt conveyors. However, with the increase in the length of the conveyor there is a need for stronger belts. This can be avoided by using intermediate drives of various designs. The article describes the principle of operation of the intermediate linear drive with transverse partitions, provides formulas for calculating the values of the tractive effort, gives comparative graphs showing the effectiveness of the use of an intermediate drive in various conditions. The possibilities of increasing the capacity of an intermediate linear drive are described.
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
ISSN: 19961073
Авторы: Koteleva, N.I, Korolev, N.A, Zhukovskiy, Y.L.

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.
publications

A soft sensor for measuring the wear of an induction motor bearing by the park’s vector components of current and voltage

Ключевые слова: ANN‐classifier | Induction motor bearing | Park’s vector | Soft sensor
Дата публикации: 2021-12-01
Журнал: Sensors
Авторы: Koteleva, N, Korolev, N, Zhukovskiy, Y, Baranov, G.

Q2

(Scimago)

This paper presents a methodology for creating a soft sensor for predicting the bearing wear of electrical machines. The technique is based on a combination of Park vector methods and a classifier based on an artificial neural network (ANN‐classifier). Experiments are carried out in la-boratory conditions on an asynchronous motor of AIR132M4 brand. For the experiment, the inner rings of the bearing are artificially degraded. The filtered and processed data obtained from the installation are passed through the ANN‐classifier. A method of providing the data into the classi-fier is shown. The result is a convergence of 99% and an accuracy of 98% on the test data.
publications

Investigation of the effectiveness of an augmented reality and a dynamic simulation system collaboration in oil pump maintenance

Ключевые слова: Augmented reality | Digitalization | Dynamic simulation | Maintenance | Oil pump
Дата публикации: 2022-01-01
Журнал: Applied Sciences (Switzerland)
ISSN: 20763417
Авторы: Koteleva, N, Valnev, V, Frenkel, I.

Q2

(Scimago)

The maintenance of oil pumps is a complex task for any operating organization, and for an industrial enterprise in the oil and gas sector of the economy, this issue has a high degree of urgency. One of the reasons for this is a wide spread of pumping equipment in all areas of oil and gas enterprises. At the same time, an aggressive environment, uneven load, remote facilities, and harsh climatic zones (especially in the areas of the Arctic region or production platforms) are factors that make it relevant to develop special systems that help or simplify the maintenance of pumping equipment. Dynamic modeling is one of the modern technologies which allows for solving the urgent issue of assessing the technical condition of equipment. It is the basis of systems that carry out diagnostics and prognostic calculations and allow for assessing the dynamic state of objects under various conditions of their operation, among other functions. Augmented reality technology is a technology that allows for reducing the time for equipment maintenance by reducing the time for searching and processing various information required in the maintenance process. This paper presents an investigation of the effectiveness of an augmented reality and a dynamic simulation system collaboration in oil pump maintenance. Since there is insufficient research on the joint application of these two technologies, the urgent issue is to prove the effectiveness of such collaboration. For this purpose, this paper provides a description of the system structure, gives a description of the development process of the augmented reality system application and tests the application using Microsoft HoloLens 2.
publications

Scenario modeling of sustainable development of energy supply in the arctic

Ключевые слова: Arctic | Energy scenarios | Energy supply | Hydrogen | Renewable energy sources | Scenario modeling | SDG-goals | Sustainability | Sustainable energy | Technological demand
Дата публикации: 2021-12-01
Журнал: Resources
ISSN: 20799276
Авторы: Zhukovskiy, Y, Tsvetkov, P, Buldysko, A, Malkova, Y, Stoianova, A, Koshenkova, A.

Q2

(Scimago)

The 21st century is characterized not only by large-scale transformations but also by the speed with which they occur. Transformations—political, economic, social, technological, environmental, and legal-in synergy have always been a catalyst for reactions in society. The field of energy supply, like many others, is extremely susceptible to the external influence of such factors. To a large extent, this applies to remote (especially from the position of energy supply) regions. The authors outline an approach to justifying the development of the Arctic energy infrastructure through an analysis of the demand for the amount of energy consumed and energy sources, taking into account global trends. The methodology is based on scenario modeling of technological demand. It is based on a study of the specific needs of consumers, available technologies, and identified risks. The paper proposes development scenarios and presents a model that takes them into account. Modeling results show that in all scenarios, up to 50% of the energy balance in 2035 will take gas, but the role of carbon-free energy sources will increase. The mathematical model allowed forecasting the demand for energy types by certain types of consumers, which makes it possible to determine the vector of development and stimulation of certain types of resources for energy production in the Arctic. The model enables considering not only the growth but also the decline in demand for certain types of consumers under different scenarios. In addition, authors’ forecasts, through further modernization of the energy sector in the Arctic region, can contribute to the creation of prerequisites that will be stimulating and profitable for the growth of investment in sustainable energy sources to supply consumers. The scientific significance of the work lies in the application of a consistent hybrid modeling approach to forecasting demand for energy resources in the Arctic region. The results of the study are useful in drafting a scenario of regional development, taking into account the Sustainable Development Goals, as well as identifying areas of technology and energy infrastructure stimulation.

Comparative wear resistance of existing and prospective materials of fast-wearing elements of mining equipment

Ключевые слова: Hadfield steel | Hardness | Mining equipment elements | Thermomechanical treatment | Wear process | Wear resistance
Дата публикации: 2021-01-01
Журнал: Materials Science Forum
ISSN: 16629752
Авторы: Bolobov, V.I, Chupin, S.A, Akhmerov, E.V, Plaschinskiy, V.A.

Q2

(Scimago)

The results of tests for resistance to abrasive wear on highly abrasive hard rock white electrocorundum are presented. The main material of fast-wearing elements of mining and processing equipment-110G13L steel (Gadfield steel) in comparison with other 9 grades of steel and cast iron, including specially developed wear-resistant foreign steels such as Hardox and Miiluks, is analyzed. The studies were carried out using an experimental stand for studying the material wearing process. On the stand the sample was fixed in a holding device and, after being brought into contact with the abrasive, it was rotated under a constant load. As a result of the experiments, it was confirmed that the order of placement of the tested materials in terms of increasing wear resistance coincides with their placement in terms of increasing hardness. At the same time, the wear resistance of the most resistant material – U8A steel after quenching – is about 4 times higher than this indicator for the least resistant components – low-carbon steel 25L, including gray and high-strength cast iron SCH21, VCH35. The wear resistance of 110G13L steel, as well as 65G, U8 steels in the hardened state, is from 1.5 to 2 times higher than that of foreign steels M400, H450, M500, H500. The results of the conducted studies allow us to evaluate the analyzed materials on the basis of their wear resistance and hardness indicators on the feasibility of using them in the manufacture of fast-wearing parts of mining equipment. Based on the research data, it seems promising to develop new ways to increase the wear resistance of domestic steel, including 110G13L steel traditionally used in mining.

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