Advertisement

Development of Hardware and Software Complex for Increase of Technical Readiness Transport-Technological Machines in Forestry

  • S. V. LyakhovEmail author
  • S. V. Budalin
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

The paper studied information technology in relation to the decision-making process in the management of the technical condition of transport and technological machines in forestry. The export of timber and forest products by road has a seasonality, which greatly limits its working time during the year. During this period, the requirements for the technical readiness of the fleet of transport-technological machines of a logging enterprise increase significantly. To reduce the downtime of transport and technological machines, it is planned to develop a software and hardware complex that works on the basis of an advisory information interactive system, which allows optimizing the time for troubleshooting and eliminating it. The implementation of the software and hardware complex in the system of maintenance and repair of transport and technological machines will increase the speed of the quality of technical decisions to ensure their performance. The paper considers the concept of creating an advising system based on deep neural networks.

Keywords

Software complex Hardware complex Transport machines Technological machines Dispatching Automation diagnostics Technical service Information system 

References

  1. 1.
    Terentyev AV (2009) Improvement of the methodology for calculating the production program of maintenance of rolling stock. Dissertation, North-Western State Correspondence Technical UniversityGoogle Scholar
  2. 2.
    Pukhov EV (2013) Improvement of the system of waste utilization by the enterprise of technical service of transport and technological machines of the agro-industrial complex. Dissertation, Voronezh State Forestry AcademyGoogle Scholar
  3. 3.
    Lyakhov SV (2012) Thesis for the degree of candidate of technical sciences. Increasing the efficiency of timber hauling by the fleet of road trains based on the planning of technical and operational indicators. Dissertation, Ural State Forestry UniversityGoogle Scholar
  4. 4.
    Budalin SV, Lyakhov SV, Nekrasov DN (2011) Calculation of the specific energy consumption of timber removal by road trains. Nat Tech Sci 6(56):572–575Google Scholar
  5. 5.
    Lyakhov SV (2011) Prediction of technical and operational indicators of timber trucks. Nat Tech Sci 6(56):586–590Google Scholar
  6. 6.
    Budalin SV, Lyakhov SV (2010) Assessment of the condition of trucks of the Sverdlovsk region. Ural Transport 1(24):32–34Google Scholar
  7. 7.
    Lyakhov SV (2012) Determination of the specific energy consumption of removal of forest raw materials and technical and operational indicators of forest truck trains. Nat Tech Sci 1:78–81Google Scholar
  8. 8.
    Nekrasov DN, Lyakhov SV, Budalin SV (2012) Algorithm for the selection of timber rolling stock for the fleet of timber enterprise. Forests Russia and the Economy in Them 1–2(42–43):67–70Google Scholar
  9. 9.
    Budalin SV, Lyakhov SV (2011) Analysis of the quality indicators of the operation of timber trucks. Nat Tech Sci 2(52):481–485Google Scholar
  10. 10.
    Klyuev V (2005) Nondestructive testing. Manual in 7 t. Under editing member’s RASV t. 7, MoscowGoogle Scholar
  11. 11.
    Lyakhov SV, Stroganov YuN (2017) To the actuality of application of the methods of investigation of vibroacoustic signals. Int Acad Agrarian Educ 34:10–14Google Scholar
  12. 12.
    Trompet GM, Aleksandrov VA (2017) Renovation of machinery and equipment. In: Materials of the All-Russian scientific and practical conference. Test results of measuring modules of active control, vol 1, pp 177–181Google Scholar
  13. 13.
    Gericke BL, Gerike PB, Kvaginidze VS, Kozovoy GI, Khoreshok AA (2012) Diagnostics of mining machines and equipment. Tutorial, MoscowGoogle Scholar
  14. 14.
    Pozhidaeva V (2005) Determining the roughness of contact surfaces of the rolling hearings by the method of shock pulses. In: World tribology congress III, Washington, D.C., 12–16 Sept 2005Google Scholar
  15. 15.
    Tse P, Peng V, Yam K (2001) Wavelet analysis and envelope detection for rolling element bearing fault diagnosis—their effectiveness and flexibilities. J Vib Acoust 123:303–310.  https://doi.org/10.1115/1.1379745CrossRefGoogle Scholar
  16. 16.
    Molchanov VV, Kamnev MI, Bocharov AG (2009) Method of repair and maintenance and hardware and software package for diagnostics and system for quality control of repair and maintenance used in the method. RUS Patent 2357215, 27 May 2009Google Scholar
  17. 17.
    Vanin AA, Razdelkin ME (2016) Control method repair actions on components and assemblies of automotive vehicles. RUS Patent 2582519, 27 Apr 2016Google Scholar
  18. 18.
    Fears AF, Kalik NA (2012) Automated control system of processes and resources for maintenance and repair. RUS Patent 2450304, 10 May 2012Google Scholar
  19. 19.
    Antonenko IN, Kubrin SS, Matyushin VA, Sukmanov AI (2013) Automation subsystem for maintenance, repair, analysis and evaluation of the technical condition of mining machines and equipment. Mining 1:68–74Google Scholar
  20. 20.
    Lyakhov SV, Stroganov YuN, Tokmancev TB (2017) Automation of maintenance and repair of transport and technological machines. Int Acad Agrarian Educ 37:22–26Google Scholar
  21. 21.
    Lyakhov SV, Stroganov YuN, Tokmancev TB (2017) The use of deep neural networks for the problem of classification of sounds. Int Acad Agrarian Educ 36:172–176Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Ural Federal UniversityEkaterinburgRussia
  2. 2.The Ural State Forest Engineering UniversityEkaterinburgRussia

Personalised recommendations