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Energy-saving Technologies and Research I Using Neural Network Models

Received: 14 June 2015     Accepted: 28 July 2015     Published: 29 July 2015
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Abstract

In article he results of researches in different aspects of surface treatment are submitted. New type of the process of stabilization of residual pressure is considered. Also new ways of hardening of details are investigated and compared. The problem of new tools and the question of its more effective using are considered. The way of neural network modeling for data processing was used for in all experiments

Published in American Journal of Neural Networks and Applications (Volume 1, Issue 1)
DOI 10.11648/j.ajnna.20150101.13
Page(s) 23-28
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Surface-active Substance, Residual Stress, Electropulse Processing, Burnishing, Neural Network, Hardening, Self-propagating High-temperature Synthesis, Nonresharpened Replaceable Many-sided Plate (Nrp), Cutting Tool

References
[1] Ambrazon A.A. The surface phenomena and surface-active substances: the Directory / A.A.Abramzon, E.D.Schukin. – L: Chemistry, 1984.
[2] Babey J.I. The physical basis of pulse hardening of a steel and pig-iron. – Kiev: Naukova dumka, 1988. – 240с.
[3] Bagmutov V. P, Parshev S.N., Dudkina N.G., Zaharov I.N. The electromechanical processing: technological and physical bases, properties, realisation. – Novosibirsk: the Science, 2003. – 318с.
[4] Jakovlev S.A., Zhiganov V. I. EMP on lathes // STIN.2000. № 6.
[5] Markauskas S.S. The electro-mechanical hardening of a surface by the tool with compulsory rotation of a roller//Researches and workings out in the field of hardening and restoration of details of cars by electromechanical processing. - Ulyanovsk, 1999.
[6] Carbide, Nitride and Boride Materials Synthesis and Processing. Ed. Alan W.Weimer, London–Weinheim–New York–Tokyo–Melburne–Madras: Chapman AND Hall, 1997, 671 pp.
[7] Corbin, N.D., and McCauley, J.W., Self-Propagating High Temperature Synthesis (SHS): Current Status and Future Prospects, MTL MS 86-1, Watertown, MA, May 1986
[8] Gah V.M. Choose of rational marks of tool materials. //Reliability of the tool and optimisation of technological systems. The collection of proceedings. - Kramatorsk: DGMA, №14, 2003
[9] Klyuev V., 2005, Non-destructive testing, Russia. Ref. / In .. Klyuyev, F.., C2 .. Rumyantsev et al., Ed. In .. Klyuev .- M. Mashinostroenie, ISBN 5-217-03300-2.
[10] http://www.Pramet.com
[11] The use of neural network techniques for condition monitoring of acoustic cutting tool / S.Kovalevsky, E.Tkachenko L.Tyutyunnik, E.Bugaev, P. Dasic // Neuro networked technologies and their applications: Proceedings of the All-Ukrainian scientific conference with international participation. - Kramatorsk: DSEA, 2013. - P. 51-54.
[12] Kovalevsky SV . Use Kohonen maps for Integrated Assessment of cutting properties of abrasive wheels / S. Kovalevsky, A.Yanyushkin, E.Bugayov // Mechanics XXI century. XI All-Russian Scientific Conference with international participation: summary reports. - Bratsk VPO "BrSU", 2012. - S. 177-180.
[13] The use of Kohonen maps for selection of inserts / E.Kovalevskaya L.Tyutyunnik E.Tulupova, D.Lobanov // Mechanics XXI century. XI All-Russian Scientific Conference with international participation: summary reports. - Bratsk VPO "BrSU", 2012. - S. 175-177.
Cite This Article
  • APA Style

    Sergiy V. Kovalevskyy, Ekaterina A. Zavgorodnyaya. (2015). Energy-saving Technologies and Research I Using Neural Network Models. American Journal of Neural Networks and Applications, 1(1), 23-28. https://doi.org/10.11648/j.ajnna.20150101.13

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    ACS Style

    Sergiy V. Kovalevskyy; Ekaterina A. Zavgorodnyaya. Energy-saving Technologies and Research I Using Neural Network Models. Am. J. Neural Netw. Appl. 2015, 1(1), 23-28. doi: 10.11648/j.ajnna.20150101.13

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    AMA Style

    Sergiy V. Kovalevskyy, Ekaterina A. Zavgorodnyaya. Energy-saving Technologies and Research I Using Neural Network Models. Am J Neural Netw Appl. 2015;1(1):23-28. doi: 10.11648/j.ajnna.20150101.13

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  • @article{10.11648/j.ajnna.20150101.13,
      author = {Sergiy V. Kovalevskyy and Ekaterina A. Zavgorodnyaya},
      title = {Energy-saving Technologies and Research I Using Neural Network Models},
      journal = {American Journal of Neural Networks and Applications},
      volume = {1},
      number = {1},
      pages = {23-28},
      doi = {10.11648/j.ajnna.20150101.13},
      url = {https://doi.org/10.11648/j.ajnna.20150101.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20150101.13},
      abstract = {In article he results of researches in different aspects of surface treatment are submitted. New type of the process of stabilization of residual pressure is considered. Also new ways of hardening of details are investigated and compared. The problem of new tools and the question of its more effective using are considered. The way of neural network modeling for data processing was used for in all experiments},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Energy-saving Technologies and Research I Using Neural Network Models
    AU  - Sergiy V. Kovalevskyy
    AU  - Ekaterina A. Zavgorodnyaya
    Y1  - 2015/07/29
    PY  - 2015
    N1  - https://doi.org/10.11648/j.ajnna.20150101.13
    DO  - 10.11648/j.ajnna.20150101.13
    T2  - American Journal of Neural Networks and Applications
    JF  - American Journal of Neural Networks and Applications
    JO  - American Journal of Neural Networks and Applications
    SP  - 23
    EP  - 28
    PB  - Science Publishing Group
    SN  - 2469-7419
    UR  - https://doi.org/10.11648/j.ajnna.20150101.13
    AB  - In article he results of researches in different aspects of surface treatment are submitted. New type of the process of stabilization of residual pressure is considered. Also new ways of hardening of details are investigated and compared. The problem of new tools and the question of its more effective using are considered. The way of neural network modeling for data processing was used for in all experiments
    VL  - 1
    IS  - 1
    ER  - 

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Author Information
  • Donbas State Engineering Academy, Faculty of integrated technology and equipment, Kramatorsk, Ukraine

  • Donbas State Engineering Academy, Faculty of integrated technology and equipment, Kramatorsk, Ukraine

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