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  8. 42-2

Electronic modeling

Vol 42, No 2 (2020)

https://doi.org/10.15407/emodel.42.02

CONTENTS

Computational Processes and systems

  SAPOZHNIKOV V.V., SAPOZHNIKOV V.Vl., EFANOV D.V.
Fault Detection in CombinationalLogic Circuits Based on Symmetrically Independent Outputs Groups Checking
3-24
  SERGIYENKO A. M., ROMANKEVICH V. A., SERHIENKO A. A.
Genetic Programming ofApplication-Specific Pipelined Datapaths
25-40
  SHEVCHENKO S.S., SHEVCHENKO O.S.
Determination of the Natural Frequencies of the Centrifugal Machine Rotor with a System of Automatic Balancing of Axial Forces
41-58

Application of Modeling Methods and Facilities

  ZUBARIEV D.O., SKARGA-BANDUROVA I.S., SAPYTSKA O.M.
Efficiency Analysis ofthe Image Optimization Algorithm for the Formation of a Database Not Confirmedby the User
59-68
  MARUSENKOVA T.A.
SPICE Model of a Logarithmic Converter for Magnetic Tracking Systems
69-90
  FARHADZADE E.M., MURADALIYEV A.Z.,RAFIYEVA T.K.,RUSTAMOVA A.A.
Branchmarkinq Power Units Tps
91-109
  SAVKA N.Ya.
Artificial Neural Networks for Modeling of Crisis Management of National Economy
109-120
  PODHURENKO V.S.,GETMANETS O.M., TEREKHOV V.E.
Mathematical Model of Wind Turbine Electricity Production As a Method of Increasing its Efficiency
121-127

 

FAULT DETECTION IN COMBINATIONAL LOGIC CIRCUITS BASED ON SYMMETRICALLY INDEPENDENT OUTPUTS GROUPS CHECKING

V.V. Sapozhnikov, V.Vl. Sapozhnikov, D.V. Efanov

Èlektron. model. 2020, 42(2):03-24
https://doi.org/10.15407/emodel.42.02.003

ABSTRACT

The main study results of the testing methods development for combinational circuits based on the properties of the codes focused on the errors detection of certain types and multiplicities are described. It is established that when using classical sum codes (Berger's code) and a number of their modifications when organizing checking of combinational circuits, it is possible to use the features of detecting unidirectional and some non-unidirectional errors in data vectors. It is shown that it is possible to search for such output’s groups on which only symmetrical errors occur due to single-error of the circuit internal structural elements. Such output groups are called symmetrically independent (SI-groups) outputs. The combinational circuit outputs group belonging conditions to the outputs SI-groups are determined. It is shown that each outputs SI-group can be controlled using a separate check subsystem based on a code with the detection of any asymmetric errors (and any asymmetric errors to certain multiplicities). Methods are proposed for searching for outputs SI-groups in combinational circuits organizing control. Particular attention is paid to the faults control at the combinational circuit’s inputs.

KEYWORDS

combinational circuit, self-checking structure, unidirectional, symmetrical, asymmetrical errors, symmetrically-independent outputs groups.

REFERENCES

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  5. Sapozhnikov, V.V., Sapozhnikov, Vl.V. and Yefanov, D.V. (2015) “Classification of errors in information vectors of systematic codes”, Izvestiya Vysshikh Uchebnykh Zavedeniy. Priborostroenie, Vol. 58, no. 5, pp. 333-343. DOI 10.17586/0021-3454-2015-58-5-333-343.
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  6. Dmitriyev, V.V., Yefanov, D.V., Sapozhnikov, V.V. and Sapozhnikov, Vl.V. (2018), “Sum Codes with Efficient Detection of Twofold Errors for Organization of Concurrent Error-Detection Systems of Logical Devices”, Avtomatika i telemekhanika, no. 4, pp. 105-122.
    https://doi.org/10.1134/S0005117918040082
  7. Sapozhnikov, V.V., Sapozhnikov, Vl.V., Yefanov, D.V. and Dmitriyev, V.V. (2017), “New structures of the concurrent error detection systems for logic circuits”, Avtomatika i telemekhanika, no. 2, pp. 127-143.
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  13. Efanov, D., Sapozhnikov, V. and Sapozhnikov, Vl. (2017) “Generalized Algorithm of Building Summation Codes for the Tasks of Technical Diagnostics of Discrete Systems”, Proceeding of the 15th IEEE East-West Design & Test Symposium (EWDTS`2017), Novi Sad, Serbia, September 29 - October 2, 2017, pp. 365-371. DOI: 1109/EWDTS. 2017.8110126.
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  19. Yefanov, D.V., Sapozhnikov, V.V., Sapozhnikov, Vl.V. (2018), “Synthesis of Self-Checking Combinational Devices Based on Allocating Special Groups of Outputs”, Avtomatika i telemekhanika, no. 9, pp. 79-94.
    https://doi.org/10.1134/S0005117918090060
  20. Sapozhnikov, V.V., Sapozhnikov, Vl.V. and Efanov, D.V. (2018), Kody Khemminga v sistemakh funktsional'nogo kontrolya logicheskikh ustroystv [Hamming codes in concurrent error detection systems of logic devices], Nauka, St. Petersburg, Russia.
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  22. Yefanov, D.V., Sapozhnikov, V.V. and Sapozhnikov, Vl.V. (2015), “Applications of Modular Summation Codes to Concurrent Error Detection Systems for Combinational Boolean Circuits”, Avtomatika i telemekhanika, no. 10, pp. 152-169.
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  24. Sapozhnikov, V., Sapozhnikov, Vl. and Efanov, D. (2017), “Search Algorithm for Fully Tested Elements in Combinational Circuits, Controlled on the Basis of Berger Codes”, Proceeding of the 15th IEEE East-West Design & Test Symposium (EWDTS`2017), Novi Sad, Serbia, September 29 - October 2, 2017, pp. 99-108. DOI: 10.1109/EWDTS. 2017.8110085.
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GENETIC PROGRAMMING OF APPLICATION-SPECIFIC PIPELINED DATAPATHS

A.М. Sergiyenko, V.A. Romankevich, A.A. Serhienko

Èlektron. model. 2020, 42(2):25-40
https://doi.org/10.15407/emodel.42.02.025

ABSTRACT

A method for the synthesis of application-specific pipeline data paths based on the genetic programming is proposed. The method consists in representing the algorithm with a spatial synchronous data flow graph, encoding its matrix of operator-nodes as chromosomes and using the genetic optimization algorithm. The high efficiency of the method is shown by the example of the discrete cosine transform processor synthesis, which is configured in FPGA.

KEYWORDS

FPGA, VHDL, SDF, data flow graph, genetic programming.

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DETERMINATION OF THE NATURAL FREQUENCIES OF THE CENTRIFUGAL MACHINE ROTOR WITH A SYSTEM OF AUTOMATIC BALANCING OF AXIAL FORCES

S.S. Shevchenko, O.S. Shevchenko

Èlektron. model. 2020, 42(2):41-58
https://doi.org/10.15407/emodel.42.02.041

ABSTRACT

The model of balancing device thrust of multistage centrifugal machine rotor that performs both functions of hydraulic seal and a radial-thrust hydrostatic bearing was considered. The linearized equations of the centrifugal pump rotor joint radial-axial vibrations with an auto rerelieving system are obtained. Expressions for defining amplitude and phase frequency characteristics are derived.

KEYWORDS

hydraulic seal, axial force balancer, joint radial-axial vibrations, frequency characteristics.

REFERENCES

  1. Martsinkovskiy, V.A. and Shevchenko, S.S. (2018), Nasosy atomnykh elektrostantsiy: raschet, konstruirovaniye, ekspluatatsiya [Pumps of nuclear power plants: calculation, design, operation], Izd-vo «Universitetskaya kniga», Sumy, Ukraine.
  2. Martsinkovsky, V.A. (2009), Osnovy dinamiki rotorov [Fundamentals of the dynamics of rotors], Sumy State University, Sumy, Ukraine.
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Efficiency Analysis of the Image Optimization Algorithm for the Formation of a Database Not Confirmed by the User

D.O. Zubariev, Post-graduate
G.E. Pukhov Institute for Modelling in Energy Engineering
National Academy of Sciences of Ukraine
(15, General Naumov Str., 03164, Kiev, Ukraine,
tel. +380996810567; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.),
I.S. Skarga-Bandurova, Doct. of Technical Sciences,
O.M. Sapytska, Cand. of Historical Sciences,
Volodymyr Dahl East Ukrainian National University
(59a, Tsentralny pr., 93400, Severodonetsk, Luhansk oblast, Ukraine,
tel. +380645228997; +380664838802;
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.)

Èlektron. model. 2020, 42(2):59-68
https://doi.org/10.15407/emodel.42.02.059

ABSTRACT

The ultimate goal of any process optimization in a particular area is to save time and human resources. The article analyzes the effectiveness of the original algorithm image processing when sampling for training artificial neural network CNN Class based on User-Confirmed Image-Dataset for needs defining image elements within binary logic.

KEYWORDS

Deep learning, Image-Dataset, image optimization function, network learning algorithm.

REFERENCES

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