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Journal archive

№2(98) March 2022 year


IT management

Performance management

Optical spectral methods in the ultraviolet and visible regions can be used to develop transformer oil control technologies based on deep learning neural network models. The aim of the research is to identify informative spectral ranges of luminescent diagnostics for the automation system for monitoring the characteristics and parameters of transformer oil using deep learning neural networks. Measurements of the spectral characteristics of pure and spent transformer oil in the range of 180-700 nm were carried out on a diffraction spectrofluorimeter "Fluorat-02-Panorama". A qualitative and quantitative difference in the excitation spectra has been established: for waste oil, the spectra are shifted to the right and reduced by about four times to the maximum. The excitation maxima are located at wavelengths of 300, 322, 370 nm for pure and 388, 416 and 486 nm for waste oil. The photoluminescence spectra of pure oil at 300 nm excitation are a superposition of at least three curves, the largest of which has a maximum at 382 nm. For excitation of 370 nm, the spectrum is significantly wider and has maxima at wavelengths of 387, 405, 433-439 and 475-479 nm. The photoluminescence spectra of used oil are several times lower and have maxima at 446, 483 and 520-540 nm. The established excitation and luminescence ranges will be used when creating a methodology and installing quality control parameters of transformer oil during its operation. A deep learning neural network model based on the use of a self-organizing Kohonen map was also developed, which made it possible to predict the spectral characteristics of excitation based on the photoluminescence flow of transformer oil and, as a result, to determine the efficiency of the described method in industry through a decision-making system.

Nowadays a production enterprise is inconceivable without the automation of all its processes – technological, production, and managerial. The efficiency of an enterprise largely depends on high-quality data processing within a single information space. The introduction of an integrated automated management system for an industrial enterprise, consistent with the business model, will eliminate many of the problems arising during creation, integration and development of automated systems, will create an effective enterprise management system and will reduce future costs of production modernization. Current trends of digital transformation increase the demand for an integrated business management system model, that would include a model of an integrated information management system as an integral part of it. The study aims to develop a reference functional model of mining enterprises, including a comprehensive vision of business, production and technological processes and their IT support. The model proposed is based on the analysis of existing international industry approaches to automation, as well as the experience and best practices of automation of mining enterprises. The methodological foundations of the research include enterprise architecture approach (including the concept of service-oriented architecture) and authors' function-oriented approach for engineering the IT architecture. The article describes a reference functional model of a mining enterprise, on the basis of which the structure of the mining enterprise IT-architecture functional structure is determined. The function-oriented approach for engineering IT-architecture as a reflection of the business functional structure is a good example of the symmetry phenomena in enterprise management. Further research will be devoted to the issues of designing an information exchange model and a data architecture model for the mining value chain and its individual parts in interconnection, as well as reflecting end-to-end processes of mining enterprises in the IT architecture based on the developed model for determining the boundaries of functional blocks of information systems.

IT and education

Educational environment

The article deals with the problem of organizing training for data scientists and data analytics specialists using information technologies. The authors analyzed the current sets of competencies of data science and analytics, identified the problems of organizing their development, considered modern trends in the instrumental support of the learning process. Particular attention is paid to the peculiarities of the development of soft skills in data science and analytics, which should be taken into account in systems and platforms for learning support when building models for the formation of personalized content and learning paths within the course. The necessity of creating a multi-agent software application to support the pedagogical design of the course is substantiated, which allows to adapt the capabilities of modern software systems and learning platforms to increase the efficiency of group interaction and the formation of soft skills necessary in the implementation of data analysis projects. The results of the conceptual design of a multi-agent application integrated with modern learning platforms are presented: a UML diagram of use cases is proposed that provides support for the personalization of training not only at the individual, but also at the command level, the base classes of agents are highlighted and an ontological model is developed to support the formation of soft skills in data science and analytics, directions of further research are determined. The results obtained will be useful to support the formation of a full set of competencies for data science and analytics, as well as to increase the efficiency of group work and support the personalization of content in a hybrid or online learning format, both in the higher education system and in corporate divisions.

Software engineering

Models and methods

The article is devoted to the issues of modeling and designing information-analytical processes corresponding to the production and technological processes at the enterprise. In the modern conditions of the functioning of the market, the enterprise faces important tasks of embedding in global supply chains, responding to an increase in the need for personalized products and, most importantly, reducing costs and improving product quality. In addition to solving these problems, the enterprise has to deal with such problems as: overproduction, waiting and wasted time, defects and marriage. Despite the fact that economic efficiency is put at the forefront, in order to ensure the sustainable development of an enterprise, it is necessary the criteria of environmental friendliness, accident-free operation and social efficiency. Enterprises, whose competitive advantages are flexibility and response speed to market needs, require tools for the operational management of production and technological processes. For effective functioning within a complex system, planning and implementation of production and technological processes must be supported by appropriate information-analytical processes that provide the collection and analysis of information, as well as modeling and making control decisions for the production and technological process. Production management is carried out in the form of strategic, tactical and operational planning, which puts forward additional requirements for modeling tools and management decision support. A variety of neuro-fuzzy Petri nets with temporal fuzzy neurons is proposed. An example of building a model of the production process and the corresponding information-analytical processes is considered. The developed specialized software for modeling production and technological processes and the implementation of information- analytical processes, including modules for forming an ontological model of a complex system and processes, obtaining data, a neural network supervisor, building a model of a production- technological process and corresponding information-analytical processes using the mechanism constructors based on neuro-fuzzy temporal Petri nets is considered.

Currently, the specifics of external conditions and peculiarities of innovation activity main subjects development determine not only the need for close, long-term scientific and technical cooperation with the state for the sustainable development of territories, but also the need to develop and substantiate proposals for managing the development of innovation processes in such a system as a whole. The article proposes a model for the representation of scientific and industrial interaction in the implementation of regional innovation processes in the form of a three-dimensional "slice" of the triple helix as a resource VRIO-profile of cooperative formation, which allows to clearly demonstrate the system of relations, identify in which direction the problem area is, influencing which it will be possible to return the system to an equilibrium state of sustainable development in a strategic perspective. The analysis of modern scientific works shows the relevance, necessity and effectiveness of using methods based on neural networks to predict changes in the state of complex socio-economic systems, such as regional innovation systems. Existing approaches, as a rule, demonstrate a narrow focus and belonging to a separate enterprise or organization, and therefore do not meet all the requirements from both the implementation of the innovation process itself and the modification of the external environment. In this connection, the authors proposed an information and analytical solution for using the described model to support decision-making on the management of cooperative formations. The developed program is based on predicting the future state (position in a three-dimensional coordinate system) of the system using deep neural networks, namely recurrent. The described practical approbation of the model can in the future serve as a basis for decision-making on the choice of forms and directions of interaction of cooperative formations in the strategic perspective.

Software engineering

Oracle programs are a key link in the interaction of blockchain systems with the outside world. They must ensure the authenticity and security of data transmitted over a computer network to blockchain smart contracts. It is possible to increase security by creating a blockchain network for oracle programs, and a consensus of independent assessments of the authenticity of data in oracle programs will ensure the security of data transmitted to the main blockchain. Blockchain control systems in real time take several milliseconds to verify the authenticity of data, to data mining and to develop a control effect on the actuators. The consensus mechanism, which requires much more time, is not acceptable in these management systems. The purpose of this work is to develop the architecture of an intelligent information system of oracle programs for a real-time blockchain management system. To achieve the goal, the following tasks were solved: analysis of the state of the problem of ensuring the reliability and completeness of data, research of the capabilities of intelligent smart contracts, research of the intellectual capabilities of peripheral computing, development of the architecture of an intelligent information system of oracle programs. The scientific novelty of the work consists in the fact that a way has been found for high-speed transmission of the reliability of data transmitted by the oracle program system to the smart contracts of the blockchain management system in real time. The practical significance of the work is to solve the problem of providing reliable data to the blockchain management system in real time.


Study of processes and systems

The article considers the existing mathematical models of magneto-rheological substances and describes some of their properties. As a result of the open sources analysis, it was found that there are no exoskeleton models with variable-length links with adjustable stiffness, based on the application of magneto-rheological fluids. Therefore, the application of these fluids in other technical systems is considered. A mathematical model of an exoskeleton variable-length link with adjustable stiffness is proposed. This link can be used for supporting and strengthening the lower limbs of the human musculoskeletal system. The difference between the proposed mathematical model of the link and the existing ones lies in the fact that the section that changes its length is considered weighty. Therefore, the mathematical model of the link with a variable inertial characteristic, the moment of inertia relative to the axis perpendicular to the longitudinal axis of the link symmetry and passing through its beginning – the point where the link is fixed to the stationary mount with a cylindrical hinge, is considered. A method of motion control based on the assignment of differentiable functions is applied. The trajectory of the link movement is found, linear and angular velocities and accelerations are calculated. To showcase the link motion, the computer-animated visualization of the link motion control problem solution is presented. The control actions required for the implementation of the given motion have been calculated in the numerical experiment. The drag coefficient range of the magneto-rheological substance has been identified during the implementation of the proposed link motion. The software implementation of the proposed mathematical model of the exoskeleton variable-length link with adjustable stiffness has been done in the Wolfram Mathematica 11.3 universal computer math environment. The software package including the unit for deriving the differential equations of motion in analytical form, the kinematic trajectory synthesis unit, the computational experiment unit, and the unit for animated visualization of the model motion and its export in the wide-spread 'gif' video format has been developed.

The article is aimed at solving the problem of scientific justification of criteria and methods for assessing the technical state of electromechanical systems based on the topological diagnostic method. Mathematical model and computer program for simulation of technical state indices of asynchronous electric motors (AEM) are presented. Functions and Green matrices, as well as deviation matrices, are considered as such indicators. The basis of the program is the mathematical model of the AEM with a non-accelerated rotor and non-homogeneous windings. AEM is supplied from pulse voltage source. The action is carried out in different directions of the vector space of the motor in order to determine its characteristics and degree of homogeneity. Based on the reactions of the object, the program calculates and analyzes technical indicators for intact and damaged states of the AEM. A computer program for mathematical modeling of the technical state indicators of the AEM was carried out using the Maple package of symbolic and numerical calculations, which provides extensive opportunities for mathematical studies of various levels. A description of a software implementation of the proposed mathematical model is given. An example of using a program to model the performance of a serial motor with specified technical characteristics is given. The article presents the results of modeling the object indicators corresponding to the object different operational states. A reference state, a damaged state characterized by a change in the properties of the vector space during long-term operation, as well as a limit state, which corresponds to a break in one of the phases of the rotor winding, were defined as these states. Conclusions on each of the given electric motor states are given.

The article deals with the issues of ontological engineering of complex systems. Ontological engineering includes the processes of designing and building ontologies, technologically combining object-oriented and structural analysis. Ontological engineering aims to ensure the adoption of high-quality management decisions by increasing the level of integration of the necessary information, improving search capabilities in databases and knowledge bases, providing the possibility of joint processing of knowledge based on a single semantic description of the knowledge space. This process is carried out within the framework of the proposed approach to managing complex systems. The ontology obtained as a result of engineering is subject to the requirements of convenience and flexibility, which is necessary for modeling system processes and ensuring the functioning of information and analytical processes in a complex system. The application of ordinary graphs, hypergraphs and metagraphs in ontological engineering is described. The use of metagraphs in the construction of hierarchical ontologies is substantiated. Metagraphs are considered as the basis for building an applied ontology of a complex system. A modification of the metagraph is proposed, which makes it possible to include events and data processing methods in the ontology. Such a modification integrates the process component into the ontological model of the system as an integral part of it, which makes it possible to flexibly and with less time to form process models based on the metagraph subgraphs of the general ontological model. An approach and an example of the implementation of the software-instrumental environment of ontological engineering and further construction of models of processes of a complex system are described. The technology used to implement the ontology in the PostgreSQL database management system and the database structure for storing the ontology are described.

Models and Methods

The article proposes a solution to the problem of accelerating the processes of self-starting of asynchronous electric motors of pumping equipment with the help of simulation computer modeling tools to reduce the negative impact on the power supply circuit of the auxiliary needs of a nuclear power plant. The features of the run-down transient processes and the interaction of machines of various capacities in the autonomous circuit that occurs after they are turned off, the subsequent transition to a backup power source, and the emerging effects during self-start are considered. It is shown that the most severe mode of such a transition occurs as a result of the operation of automatic switching on of the reserve and disconnection of working power sources by technological protections or actions of operational personnel at the operational level of operating voltage and nominal or close to it load sections. The analysis of emerging modes is carried out using models developed in the MatLab computer mathematics system with a built-in electrical application. The features of the processes of run-down and subsequent self-starting at various favorable and unfavorable moments of time and the magnitude of the mismatch between the voltages of the network and the resulting autonomous circuit are demonstrated. The models make it possible to obtain a reliable mathematical description of the electromagnetic and mechanical processes of motors in a complex electromechanical system of several motors, to measure the instantaneous voltage differences between the network and the run-down circuit, and to predict the optimal time to turn on the backup power source. The results of the studies carried out on the models are the development of recommendations on the technology for monitoring voltage and circuit mismatches for the same phases, the assessment of the root-mean-square deviation of these mismatches and the effective search for the moment of re-enabling the backup source to improve the technological modes of nuclear power plants.