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• DETERMINING THE RELIABILITY OF THE INSTRUMENT SPEED PARAMETER BASED ON THE DYNAMIC CHARACTERISTICS OF THE OBJECT OBTAINED DURING FLIGHT TESTS

  А.А. Zadorozhniy

  2022-03-02

  Abstract ▼

  The article describes about of the typical methods of air data parametric quorum control,
  and an analysis of their capabilities to determine parametric failures that occur in the air data
  system. To perform the calculations, the most common types of failures of the path of perception
  and measurement of air pressure of the air signal system, causing catastrophic consequences,
  were selected, the physical principles of their occurrence were described, the implementation of
  which made it possible to build mathematical models of signal distortion. Based on the results of
  modeling the operation of typical quorum control methods, and their response to failures artificially
  introduced into the system, the advantages and disadvantages of the methods used are determined.
  In order to eliminate the shortcomings found as a result of the analysis, an alternative
  method for determining failures of the sensor group of the air data system is proposed by implementing
  cross-checking of the parameters obtained from the pneumatic and vane sensor groups of
  the system. For the proposed method, the results of modeling based on real flight data of a mainline
  aircraft with parametric failures artificially introduced into them are presented. The possibility
  of using the cross-checking algorithm in single-channel systems of air signals of small-sized
  aircraft is evaluated. The statement of the research problem is formulated as follows: in order to
  ensure the flight safety of an aircraft when using information in the control loop from a singlechannel
  air data system, it is necessary to ensure the detection and exclusion of unreliable data
  from the array of information issued by the system to consumers of information. At the same time,
  the task of detecting and excluding data must be solved by the air data system itself, without using
  additional data from other aircraft systems. Mathematical analysis, numerical modeling, determination
  of correction factors and preparation of initial data were carried out in the MathCAD software
  and mathematical complex. Analysis of the results of the studying implemented in the
  MathCAD PMC cross-checking algorithm showed that the problem of determining the reliability
  of information can be solved autonomously when it implemented a single-channel system of air
  signals in an aircraft.

• DESTRUCTURIZATION OF CRITICAL INFORMATION INFRASTRUCTURE FOR ASSESSING THE INFRASTRUCTURAL STABILITY OF THE SUBJECT OF CRITICAL INFORMATION INFRASTRUCTURE UNDER DESTRUCTIVE INFLUENCES

  Е. А. Maksimova, N. P. Sadovnikova

  2021-11-14

  Abstract ▼

  With the adoption of Federal Law No. 187 "On the Security of Critical Information Infrastructure",
  the implementation of which in practice is not possible without a comprehensive assessment
  of information security (IS) of subjects of critical information infrastructure (SСII).However, the currently existing regulatory documents of regulators do not consider SСII from the
  point of view of a systematic approach, the infrastructural component of SСII is not taken into
  account when building an information protection system. At the same time, the assessment of IS
  SСII without taking into account the effect on the state and behavior of the system of inter-object
  and intersubject connections arising in the system leads to an error in the assessment, since the
  system itself, under certain conditions, can generate infrastructural destructivism. Thus, the error
  in assessing the ISSII arises due to the failure to take into account the indicator of the SСII's inability
  to implement its functionality in full under the influence of infrastructure risks, i.e. infrastructural
  destructivism. From the point of view of the theory of sustainability, this indicator can
  be correlated with the category of “infrastructure sustainability of SСII”. The proposed by the
  authors of the study, the model for assessing the infrastructure sustainability (IS) of SСII is presented
  1) using the apparatus of cognitive modeling, 2) using the apparatus of the theory of reliability
  of technical systems. Within the framework of cognitive modeling, the power of concepts is
  set by experts. In the presented study, for this assessment, it is proposed to use the apparatus of
  logical-probabilistic modeling, through a clear structuring of the system - SСII. Thus, the assessment
  of the infrastructure stability of the SCII is characterized by the possibility of assessing the
  probability of no-failure operation of the facilities of the CII and preventing failures in the functioning
  of the CII spheres, which guarantees stability and the required level of information security.
  In this case, the problem of assessing IS in this case acquires a key character in the comprehensive
  assessment of IS SСII.

• INVESTIGATION OF STRUCTURAL CHARACTERISTICS OF DISTRIBUTED COMPUTING SYSTEMS BASED ON GRAPHS WITH MULTIPLE EDGES OF DIFFERENT TYPES

  E.R. Muntyan , E.V. Melnik

  2021-08-11

  Abstract ▼

  The article considers the issues of fault-tolerant computing systems (CS) development in
  terms of their structure and redundancy. It is necessary to take into account a great amount of
  factors, which have an impact on performance, reliability and fault tolerance, during the distributed
  CS development. For distributed CS such factors contain, among other things, structural characteristics.
  The dependency graphs of processor nodes (PN)nonfailure operating probability of
  distributed CS against system structural characteristics are presented in the article. The application
  of advanced redundancy methods, such as performance redundancy, increases the complexity
  of structure design problem. In the case of performance redundancy, instead of adding redundant
  nodes to the system, it is proposed to use redundant computational resources among the involved
  processor nodes. If a node fails, its tasks are reallocated to a free reserve of nodes, which are able
  to work. To implement this method of system redundancy, the organization of a multi-program
  operation mode is required, when some tasks can be performed simultaneously on each node.
  Need for multi-program operation mode providing leads to increasing the number of system configurations, which have to be analyzed on the design stage and in the case of reconfigurations
  when a failure takes place. To reduce the labour intensity of a configuration analysis an approach
  based on graphs with multiple edges of different types is proposed. The use of models based on
  such graphs makes it possible to represent the structure of CS taking into account a multi-program
  operation mode and at the same time significantly reduce the computational time of basic characteristics
  by means of applying relations in the form of a vector, which allows to integrate some
  relations of different types.

• ALGORITHM FOR TRAINING THE ARTIFICIAL NEURAL NETWORK OF FACTOR PREDICTING THE POWER CABLE LINES INSULATING MATERIALS LIFE

  N.K. Poluyanovich, M. N. Dubyago

  2021-07-18

  Abstract ▼

  The article is devoted to the research of thermofluxtual processes in accordance with the
  theory of thermal conductivity for solving the problems of factor prediction of the residual life of
  insulating materials based on the non-destructive temperature method. The relevance of the task of
  developing algoritma for predicting the temperature of SCL cores in real time based on the data of
  the temperature monitoring system, taking into account the change in the current load of the line
  and external heat removal conditions, is justified. The experimental method revealed the types of
  artificial neural networks, their architecture and composition, which provide maximum prediction
  accuracy with a minimum set of significant factors. A neural network has been developed to determine
  the temperature regime of the current-carrying core of the power kawhite. The minimum
  set of significant factors and the dimension of the input training vector is determined, which provides
  the versatility of the neural network prediction method. A neural network for determining the
  temperature mode of the current-carrying core is designed to diagnose and predict the electrical
  insulation (EI) life of a power cable. The model allows assessing the current isolation state and
  predicting the residual resource of the SCL. Comparative analysis of experimental and calculated
  characteristics of learning algorithms of isostic neural is carried out. It has been found that the
  proposed algorithm of artificial neural network can be used for prediction of current-carrying
  core temperature mode, three hours in advance with accuracy up to 2.5% of actual value of core
  temperature. The main field of application of the developed neural network for determining the
  temperature mode of the current-carrying core is in di-agnostics and predicting the electrical
  insulation (EI) life of the power cable. The development of an intelligent system for predicting the
  temperature of the LCS core contributes to the planning of the operation modes of the electric
  network in order to increase the reliability and energy efficiency of their interaction with the integrated
  energy system.

• THERMOFLUCTUATION THEORY OF DESTRUCTION AND EVALUATION DURABILITY OF ELECTRICAL INSULATION OF SPE CABLES

  N.K. Poluyanovich, M.N. Dubyago, D.V. Burkov

  2022-01-31

  Abstract ▼

  The article is devoted to research on the creation of a method for assessing the durability of
  the main insulation of power cable lines based on the thermofluctuation theory of destruction of solids.
  The features of breakdown development in homogeneous and inhomogeneous dielectrics are
  considered. The problematic issues of insulating materials of power cable systems (PCS) are considered
  on the basis of the development and development of non-destructive testing methods. The main
  components that destroy the insulation of the PCS are installed. The thermofluctuation theory of
  destruction and the evaluation of the durability of electrical insulation of power cables are described.
  An analytical method is proposed for evaluating the processes of cellulose oxidation with the determination
  of the most probable. The proposed approach to identifying the main processes of insulation
  destruction allows us to present in more detail the prerequisites for the development of partial discharges
  (PD) in isolation and to determine measures to minimize the processes leading to the destruction
  of PCS insulation. The results of experiments on the study of the service life of the insulating
  material of aged ends of a power cable in a thermal cabinet, to determine the aging criteria, are
  presented. The experimental data are interpreted from the standpoint of the thermofluctuation theory.
  The dependence of the increase in the temperature difference ΔT on the degree of wear of the electrical
  insulating properties of the material is revealed and investigated, which makes it possible to predict
  its resource. The thermofluctuation theory of the destruction of insulating materials caused by
  the thermofluctuation rupture of chemical bonds and the evaluation of the durability of electrical
  insulation of cables made of cross-linked polyethylene are considered. It is shown that, in order to
  calculate the average energy of the monomeric link of various polymer materials, it is necessary to
  know: the chemical formula of the monomeric link and the values of the binding energies. In the
  work, the time before the breakdown of the main insulation of the PCS was determined under the
  action of temperature. The model can be used in devices and systems for continuous diagnosis of
  power cables according to temperature conditions.

• DEVELOPMENT OF A RELIABLE RTC COMMUNICATION METHOD BASED ON A GROUP DATA SEPARATION METHOD BASED ON A RESIDUAL CLASS SYSTEM

  Y.N. Kocherov, D.V. Samoilenko

  2021-04-04

  Abstract ▼

  The paper considers a reliable method of data transmission in commu-nication systems and
  control of robotic complexes. Due to the fact that a change in part of the encoded information
  transmitted through com-munication channels can lead to partial or complete loss of data and, as
  a consequence, lead to loss of control over the robotic complex. There-fore, it is necessary to apply methods of protecting data transmitted over radio channels. The proposed method is intended
  to ensure the protection of information in the communication channels of robotic complexes from
  the access of unauthorized users and to confirm the reliability of the information received.
  The article examines data protection methods designed to protect in-formation circulating in systems
  formed by several interacting agents. The approach under consideration is based on the
  methods of infor-mation protection and error-correcting coding based on the system of residual
  classes. The applied methods of error-correcting coding, based on the system of residual classes,
  are based on the idea of threshold data separation, in which the original information can be restored
  from parts of the original information. This is due to the fact that redundant modular
  arithmetic, or redundant system of residual classes, has unique properties with re-spect to error
  detection and correction. In addition, the system of resid-ual classes has such an advantage as low
  computational complexity of data separation algorithms. To increase the reliability of communication
  between robotic complex-es in multichannel communication systems, the paper proposes a
  meth-od for information protection and noise-resistant coding, based on a multistage threshold
  data separation. As a result of the work, a system of noise-resistant information trans-mission was
  obtained, which provides comprehensive protection for robotic systems.

• LOGICAL RESYNTHESIS OF COMBINATIONAL CIRCUITS FOR RELIABILITY INCREASE

  N. O. Vasilyev , M.A. Zapletina , G. A. Ivanova , A.N. Schelokov

  2020-11-22

  Abstract ▼

  The external influences are necessary to take into account for microelectronic devices operating
  in space. In these conditions, the operation of the device is hampered by the negative
  effect of radiation on the electronic components of the circuit. Exposure of heavy charged part icles
  leads to single faults of logic elements due to which the operation of a whole device can be
  violated. In this regard, the designed spacecraft electronic circuits must meet increased r equirements
  for the fault tolerance of integrated circuits (ICs). The decrease of technological
  design standards for ICs makes the problem of fault tolerance to be relevant for civilian microelectronic
  products, also. The solution to this problem is usually carried out by methods of
  hardware protection, which include methods of error-correcting coding, methods of redundancy,
  as well as methods of logical protection. The paper considers the methods for assessing the
  IC tolerance to single faults in logic elements, as well as the main methods of circuits failure
  protection. The paper proposes a resynthesis technique for logical combinational circuits, using
  logical constraints derived from the resolution method to assess the IC resistance to single faults.During resynthesis, it is proposed to use the methods of logical protection of vulnerable parts of
  the circuit. This does not cause a perceptible increase in the area occupied by the device unlike in
  methods of redundancy and error-correcting coding.

• ASSESSMENT OF INFLUENCING FACTORS AND FORECASTING OF POWER CONSUMPTION IN THE REGIONAL POWER SYSTEM, TAKING INTO ACCOUNT ITS OPERATING MODE

  N.K. Poluyanovich, М. N. Dubyago

  2022-05-26

  Abstract ▼

  The article is devoted to the research of the assessment of influencing factors and forecasting
  of power consumption in the regional power system, taking into account its operating modes.
  The analysis of existing methods of forecasting energy consumption is carried out. The choice of a
  forecasting method using an artificial neural network is justified. An algorithm for creating a neural
  network for short-term prediction of electrical load is considered. The relevance of the work is
  due to the requirements of the current legislation for forecasting electricity consumption in order
  to solve the problem of maintaining a balance of power between the generating side and the consumption
  of electric energy. At the same time, one of the main tasks related to the generation of
  electric energy and its consumption is the task of maintaining a balance of capacities. On the one
  hand, with an increase in the planned load, interruptions in the supply of electricity may occur, on
  the other hand, a decrease in electricity consumption will also lead to a decrease in the efficiency
  of power plants, and ultimately to an increase in the cost of electricity both for the wholesale electricity
  market and for the end user. The developed neural network model reduces the task of shortterm
  forecasting of power consumption to the search for a matrix of free coefficients by training
  on available statistical data (active and re-active power, ambient temperature, date and index of
  the day). The received NS model of short-term forecasting of power consumption of a section of
  the district 10 kV electric grid takes into account the factors: – time, - meteorological conditions,
  – disconnections of individual power supply lines of cottages, – operating mode of electricity consumers.
  Predictive estimates of the power consumption of the power system have been obtained
  based on the data of the electricity consumed by the outdoor temperature, the type of day, etc. The
  model for predicting the magnitude of the consumed active and reactive power is quite workable,
  but at this stage still has a fairly high level of forecasting error. To improve the accuracy of forecasting,
  it is necessary to increase the database that makes up the training sample, because at the
  moment the available data cover a time period of only 3–4 months. The results of the analysis
  showed that forecasting reactive power consumption causes the greatest difficulties.

• METHODOLOGY AND RELIABILITY MODELING OF THE GROUP CONTROL SYSTEM FOR ROBOTIC PLATFORMS

  A. S. Boldyrev, A. L. Verevkin, K. V. Pshikhopova , L. S. Verevkina

  2020-10-11

  Abstract ▼

  One of the most relevant areas of robotics development is the design of group cont rol
  systems. In the proposed structure, a group of five robotic platforms (RP) is controlled from a
  wearable or stationary remote control. This composition of the group determines schemeswith tunable connections between the components and changes in the principles of operation.
  The article presents experimental studies of the computational efficiency of methods for planning
  RP trajectories in space and defines the optimal method and the required parameters of
  the RP computer. Variants of schemes with different numbers of RP are considered, as well
  as models of cold backup of RP, remote controls, and the entire system. With such a variety
  of configurations, problems arise in justifying and selecting calculation methods, and in
  providing an unambiguous, generalized representation of the reliability parameters of a
  group control system. Increased requirements for the reliability of components of the group
  management system require an accurate assessment of reliability and are dictated by the
  significant cost of equipment and functional purpose. The developed method is intended for
  modeling the reliability of the developed system of group control of robotic platforms RP.
  The proposed method shows the use of structural, probabilistic and matrix methods for ca lculating
  reliability models of a group control system. An approach to modeling the reliabi lity
  of integer, redundant, sliding, and cold redundancy of RP and control panels is also pr oposed.
  The results of numerical calculations of the reliability parameters of the group management
  system allow us to assess the risks and choose modes, depending on the required
  efficiency of the mission.

• MULTI-STAGE METHOD FOR SHORT-TERM FORECASTING OF TEMPERATURE CHANGES MODES IN THE POWER CABLE

  N.K. Poluyanovich, N.V. Azarov, A.V. Ogrenichev, M.N. Dubyago

  2020-07-20

  Abstract ▼

  The article is devoted to research on the creation of diagnostics and prediction of
  thermofluctuation processes of insulating materials of power cable lines (PCL) of electric power
  systems based on such methods of artificial intelligence as neural networks and fuzzy logic. The
  necessity of developing a better methodology for the analysis of thermal conditions in PCL is
  shown. The urgency of the task of creating neural networks (NS) for assessing the throughput,
  calculating and predicting the temperature of PCL conductors in real time based on the data of
  the temperature monitoring system, taking into account changes in the current load of the line and
  the external conditions of the heat sink, is substantiated. Based on the main criteria, traditional
  and neural network algorithms for forecasting are compared, and the advantage of NS methods is
  shown. The classification of NS methods and models for predicting the temperature conditions of
  cosmic rays has been carried out. The proposed neural network algorithm for predicting the characteristics
  of electrical isolation was tested on a control sample of experimental data on which
  training of an artificial neural network was not carried out. The forecast results showed the effectiveness
  of the selected model. To solve the problem of PCL resource prediction, a network was
  selected with direct data distribution and back propagation of the error, because Networks of thistype, together with the activation function in the form of a hyperbolic tangent, are to some extent a
  universal structure for many problems of approximation, approximation, and forecasting. A neural
  network was developed to determine the temperature regime of a current-carrying core of a power
  cable. A comparative analysis of the experimental and calculated characteristics of the temperature
  distributions was carried out, while various load modes and the functions of changing the
  cable current were investigated. When analyzing the data, it was determined that the maximum
  deviation of the data received from the neural network from the data of the training sample was
  less than 2.2 %, which is an acceptable result. The model can be used in devices and systems for
  continuous diagnosis of power cables by temperature conditions.

• ANALYSIS AND SELECTION OF METHODOLOGIES IN THE SOLUTION OF THE PROBLEMS OF INTELLECTUALIZATION IN SYSTEMS FOR PROGNOSIS OF THERMOFLUCTUATION PROCESSES IN CABLE NETWORKS

  N.K. Poluyanovich, M.N. Dubyago

  2020-07-20

  Abstract ▼

  The article is devoted to research on the creation of diagnostics and prediction of
  thermofluctuation processes of insulating materials of power cable lines (PCL) of electric power
  systems based on such methods of artificial intelligence as neural networks and fuzzy logic. The
  necessity of developing a better methodology for the analysis of thermal conditions in PCL is
  shown. The urgency of the task of creating neural networks (NS) for assessing the throughput,
  calculating and predicting the temperature of PCL conductors in real time based on the data of
  the temperature monitoring system, taking into account changes in the current load of the line and
  the external conditions of the heat sink, is substantiated. Based on the main criteria, traditional
  and neural network algorithms for forecasting are compared, and the advantage of NS methods is
  shown. The classification of NS methods and models for predicting the temperature conditions of
  cosmic rays has been carried out. To solve the problem of forecasting the PCL resource, a network
  was selected with direct data distribution and back propagation of the error, because networks of this type, together with an activation function in the form of a hyperbolic tangent, are to
  some extent a universal structure for many problems of approximation, approximation, and forecasting.
  A neural network has been developed to determine the temperature regime of a currentcarrying
  core of a power cable. A comparative analysis of the experimental and calculated characteristics
  of the temperature distributions was carried out, while various load modes and the
  functions of changing the cable current were investigated. When analyzing the data, it was determined
  that the maximum deviation of the data received from the neural network from the data of
  the training sample was less than 2.5 %, which is an acceptable result. To increase the accuracy, a
  large amount of input and output data was used when training the network, as well as some refinement
  of its structure. The model allows you to evaluate the current state of isolation and predict
  the residual life of PCL. The model can be used in devices and systems for continuous diagnosis
  of power cables by temperature conditions.

• MATHEMATICAL MODEL FOR CALCULATING RELIABILITY INDICES OF SCALABLE COMPUTER SYSTEMS WITH SWITCHING TIME

  V.A. Pavsky, K.V. Pavsky

  2020-07-20

  Abstract ▼

  The main feature of scalable computer systems is modularity. Increasing performance in
  such systems is achieved by increasing the same type of elements, elementary machines (EM, for
  example, a computing node). As a result of failures, the system performance is changed. Thus,
  scalability of computer systems (CS), on the one hand, increases performance, but on the other
  hand, computer resource growth exacerbates the problem of reliability and increases the complexity
  of organizing effective functioning. Analysis of reliability and potential capabilities of computing
  systems is still an urgent problem. For quantitative analysis of the functioning of scalable
  computing systems, robustness indices related to reliability are used. For example, indices of potential
  robustness of CS take into account the fact that all operable elementary machines are used
  in solving tasks, the number of which (EM) changes over time as a result of failures and recoveries.
  When analyzing reliability, models based on the theory of Markov processes and Queuing
  theory (QT) are popular in the theory of computing systems. Most QT analytical models do not
  consider the switching time (reconfiguration) in a separate parameter, due to the complexity of thesolution. Usually, models are simplified by the fact that the recovery time and switch combined in a
  single parameter. Analytical solutions of a system of differential equations with three parameters
  (failure, recovery, and switching) for calculating reliability and potential robustness are obtained on
  the example of the QT model. This allows the user to determine whether the switching time should be
  taken into account. Also it is shown that solutions of the three-parameter model are reduced to solutions
  of the two-parameter model if the switching time is not taken into consideration.

• ANALYSIS OF THE EFFECTIVENESS OF TRADITIONAL AND MODERN TECHNOLOGIES FOR MONITORING POWER TRANSMISSION LINES

  О. V. Afanaseva , Т.F. Tulyakov

  182-188

  2025-10-01

  Abstract ▼

  The article provides a comprehensive analysis of the effectiveness of traditional and modern technologies for monitoring power transmission lines (PTL). Power transmission lines are a critical element of the energy infrastructure, and their reliable operation directly affects economic stability and safety. Traditional monitoring methods, such as visual inspections and mechanical devices, have long remained the main control tools, but their limited accuracy, high dependence on the human factor and the inability to promptly detect hidden defects make them less effective in the face of increasing loads on power systems. Modern technologies, including unmanned aerial vehicles (UAVs), the Internet of Things (IoT), automated monitoring systems and digital twins, offer fundamentally new opportunities for monitoring the condition of PTLs. They provide high diagnostic accuracy, continuous data collection in real time, reduced operating costs and increased personnel safety. The article presents a classification of both traditional and modern methods, as well as a comparative analysis of their key parameters: accuracy, response speed, cost, safety and impact on operation. The results of the study demonstrate that modern technologies outperform traditional approaches in all the criteria considered. In particular, the use of IoT and UAVs allows minimizing the human factor, reducing inspection time and increasing data detail. Digital twin systems make it possible to predict possible accidents and optimize scheduled maintenance. However, successful implementation of innovative solutions requires additional investment, personnel training and integration with existing management systems. The conclusion is made about the strategic importance of switching to modern power transmission line monitoring technologies to improve the reliability and sustainability of the energy infrastructure. Despite high initial costs, their long-term benefits, including reduced accidents, resource savings and increased safety, fully justify the investment. The authors emphasize the need for further development of digital technologies in the energy sector to ensure stable and efficient operation of power grids

• COMPUTATIONAL FORENSICS METHODOLOGY AND FORMAL VERIFICATION OF EXPERT FINDINGS

  Е.S. Abramov

  45-68

  2026-07-07

  Abstract ▼

  This paper addresses the fundamental challenge of overcoming the systemic epistemological crisis in digital forensics. This crisis is driven by an expanding semantic gap between the probabilistic and stochastic nature of digital traces—frequently compromised by anti-forensic techniques—and the rigorous demands of adversarial legal proceedings for the legal certainty of evidence. The article is conceptual in nature and establishes the theoretical foundation of computational forensics as an independent scientific discipline. The study justifies a necessary paradigm shift from traditional heuristic artifact-discovery approaches and subjective expert opinions toward a rigorous methodology grounded in the principles of algorithmic reproducibility, the measurability of uncertainty, and formal verifiability. The author develops a set-theoretic ontological model of a computer incident, which is built upon the "subject–method–object" (S-M-O) triad and the axiom of process trace conservation. This model enables a one-to-one mapping of low-level technical indicators (IoA, IoB, IoC) onto the legal elements of a crime (corpus delicti). Furthermore, a methodology for the formal verification of hypothesis validity is proposed, incorporating the criteria of structural completeness, causal coherence, logical consistency, and factual grounding. For the first time, a mathematical model for assessing the reliability of expert findings using a logistic function (trust function) is introduced into scientific discourse. This model enables the calculation of the probability of a juridical fact by aggregating taxonomic compliance metrics, the strength of causal relationships within the incident graph, and an environmental entropy penalty. The application of the developed approach transforms forensic incident reconstruction from an ill-posed inverse problem into a deterministic procedure, ensuring the mathematically provable objectivity of the evidentiary base even under conditions of incomplete data and active anti-forensic countermeasures.

• ADAPTIVE SYSTEM FOR CONTROLLING TECHNICAL CONDITION WITH MULTIPLE-CURRENT MEASUREMENT PATHS

  D.L. Tukeev , Е. V. Kramarev , О.V. Afanaseva , D. А. Pervukhin

  254-264

  2026-07-07

  Abstract ▼

  The current stage of development in the methodology for analyzing and synthesizing complex technical systems is characterized by a substantial increase in requirements for their design speed without a loss of functional quality. This is achieved through the application of information technologies for designing complex systems and modeling their operation processes. Within this paradigm, solving the problem of creating adaptive multi-agent systems for monitoring the technical condition of highly critical objects appears relevant. These systems would use a set of varying-accuracy measurement channels for each type of monitored parameter. This will enable the operational selection of a measuring instrument and the formation of the most rational monitoring algorithm, ensuring the required monitoring effectiveness under significant financial constraints. The aim of this work is to substantiate the possibility of using varying-accuracy measurement channels when forming the structure of each technical condition monitoring channel to ensure a given reliability. To achieve this aim, the following tasks were set and successfully solved: – modern conditions for designing technical condition monitoring systems for complex technical systems were considered; constraining factors and trends in design theory development were identified; causes of potential shortcomings in prospective systems and ways to eliminate them were determined;– the form of the system performance criterion was defined as a generalized indicator, obtained based on an additive convolution of unit unconditional monitoring reliability indicators and weight coefficients of their importance; – a structural diagram of an adaptive system was synthesized based on a model of a single-parameter monitoring channel with measurement tracts of different accuracy and the capability to implement known methods for improving monitoring effectiveness; – a computational experiment was conducted, the results of which allowed for refining the identified patterns and proposing new recommendations. The results of the conducted research enabled the development of an adaptive algorithm for monitoring a multi-parameter Object of Control based on a multi-agent system. The behavior of its agents is modeled using retrospective information from previous monitoring cycles, predictive models based on this information, as well as the implementation of the principle of equal reliability and penalty functions in case of deviation from it.

• MATRIX METHOD FOR SIMULTANEOUS RELIABILITY ASSESSMENT OF COMPLEX MULTI-AGENT RECOFIGURABLE SYSTEMS

  V.K. Pshikhopov , А. L. Verevkin , А.R. Gaiduk , L.S. Verevkina

  249-259

  2026-09-10

  Abstract ▼

  The article presents the developed matrix method of simultaneous assessment of the reliability of several variants of complex multi-agent reconfigurable systems, as well as the staged method of reservation, which differ from the known ones in their simplicity and wide scope of application The matrix reliability assessment method consists in a matrix display of the reliability parameters of all agents of a specific variant of a group of system agents and a vector representation of the mission conditions. It is assumed that the mission reliability of a target group of agents is determined solely by the reliability of the agents themselves and the nature of their redundancy. The staged redundancy method is distinguished by its use of traditional standard redundancy schemes as stages in the process of redundant agent groups, significantly increasing the reliability of system variants. System agents are divided into active agents, directly performing the current mission, and passive agents, awaiting activation. Active agents, in turn, are divided into primary and backup agents. Primary agents initiate mission execution, while backup agents, awaiting replacement of failed active agents, can be in either an active state (hot standby) or a cold standby state. Specific mission conditions are taken into account by a vector of correction factors, significantly improving the accuracy of reliability assessment and agent group uptime prediction. An important feature of the proposed methods for assessing and predicting reliability is their analytical nature, which allows the use of modern high-speed computing tools in solving problems of ensuring the required reliability of missions performed by complex multi-agent systems

• ANALYSIS OF CHARACTERISTIC FOR CED CIRCUITS BASED ON REDUNDANT ENCODING METHODS

  D. V. Telpukhov , T. D. Zhukova, A. N. Schelokov

  2020-11-22

  Abstract ▼

  Typically, soft errors that occur in electronic equipment under influence of various destabilizing
  factors, were under the scrutiny of memory element developers. But recent research in this
  area shows that with development of microelectronics, the number of soft errors in combination
  circuits is increasing and soon their frequency of occurrence will be comparable to that in unprotected
  memory elements. Presently, to address this problem, special attention has been paid to
  methods based on control devices. These methods, by introducing additional structural redundancy,
  enable scheme to automatically detect and/or correct errors that occur in it. However, as a
  result of application of various methods of synthesis concurrent error detection (CED) circuits
  depending on initial parameters and internal structure of protected scheme devices possessing
  various efficiency and reliability characteristics are realized. However, as a result of application
  of various methods of synthesis CED circuits depending on initial parameters and internal structure
  protected circuit, the devices possessing different efficiency and reliability characteristics are
  realized. That is why there is a necessity to define and develop evaluation functions for analysis inorder to find the best method of synthesis CED circuit for certain device without any preliminary
  modeling. This work is devoted to development specification of structural redundancy and reliability
  characteristics evaluation functions on the example of CED circuits on basis of spectral and lowdensity
  parity-check code. The comparative and correlation analysis of analytical data with experimental
  values was carried out to evaluate efficiency of the functions obtained as a result of study.