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Development of Hardware-Algorithmic System for ICE Diagnostics

  • L. A. GaliullinEmail author
  • R. A. Valiev
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

Recently, the research in the development of methods and tools for the diagnosis of internal combustion engines is conducted in the direction that determines the use of modern technical and information systems. A significant part of the work associated with the study of internal combustion engines in transitional operating modes. At the same time, it is noted that it is difficult to carry out experimental studies related, as already noted, with the high cost of equipment, its low distribution and high labor costs for conducting experiments, and in some cases with insufficient accuracy of measurement and data processing. High labor costs are associated primarily with the need to install the engine in special stands and the use of special sensors. The systems based on the possibilities of self-diagnosis of an internal combustion engine with an electronic control system do not allow obtaining engine characteristics in the whole range of rotational frequencies, i.e., have low information content. Thus, there is a need to develop a system for diagnosing internal combustion engines, which ensures sufficient accuracy and informational content of experimental studies, has a low cost and low labor costs, and allows investigating the engine in various operating modes.

Keywords

Engine Diagnostic Testers Model System 

References

  1. 1.
    Shah M, Gaikwad V, Lokhande S, Borhade S (2011) Fault identification for I.C. engines using artificial neural network. In: Proceedings of 2011 international conference on process automation, control and computing, PACC 2011, art. no. 5978891Google Scholar
  2. 2.
    Galiullin LA, Valiev RA (2016) Modeling of internal combustion engines test conditions based on neural network. Int J Pharm Technol 8(3):14902–14910Google Scholar
  3. 3.
    Wei D (2011) Design of Web based expert system of electronic control engine fault diagnosis. In: BMEI 2011—Proceedings 2011 international conference on business management and electronic information, 1, art. no. 5916978, pp 482–485Google Scholar
  4. 4.
    Galiullin LA, Valiev RA (2018) An automated diagnostic system for ICE. J Adv Res Dyn Control Syst 10(10):1767–1772Google Scholar
  5. 5.
    Valiev RA, Galiullin LA, Dmitrieva IS, Ilyukhin AN (2015) Method for complex web applications design. Int J Appl Eng Res 10(6):15123–15130Google Scholar
  6. 6.
    Galiullin LA, Valiev RA (2018) Method for neuro-fuzzy inference system learning for ICE tests. J Adv Res Dyn Control Syst 10(10):1773–1779Google Scholar
  7. 7.
    Zubkov EV, Galiullin LA (2011) Hybrid neural network for the adjustment of fuzzy systems when simulating tests of internal combustion engines. Russ Eng Res 31(5):439–443CrossRefGoogle Scholar
  8. 8.
    Galiullin LA, Valiev RA (2018) Modeling of internal combustion engines by adaptive network-based fuzzy inference system. J Adv Res Dyn Control Syst 10(10 Special Issue):1759–1766Google Scholar
  9. 9.
    Galiullin LA, Valiev RA (2018) Optimization of the parameters of an internal combustion engine using a neural network. J Adv Res Dyn Control Syst 10(10 Special Issue):1754–1758Google Scholar
  10. 10.
    Galiullin Lenar A, Valiev Rustam A (2017) Diagnosis system of internal combustion engine development. Rev Publicando 4(13):PR128–PR137Google Scholar
  11. 11.
    Galiullin Lenar A, Valiev Rustam A, Mingaleeva Lejsan B (2018) Development of a neuro-fuzzy diagnostic system mathematical model for internal combustion engines. HELIX 8(1):2535–2540CrossRefGoogle Scholar
  12. 12.
    Galiullin Lenar A, Valiev Rustam A (2017) Mathematical modelling of diesel engine testing and diagnostic regimes. Turkish Online J Design Art Commun 7:1864–1871Google Scholar
  13. 13.
    Galiullin LA, Valiev RA (2017) Diagnostics technological process modeling for internal combustion engines. In: 2017 International conference on industrial engineering, Applications and Manufacturing (ICIEAM)Google Scholar
  14. 14.
    Guihang L, Jian W, Qiang W, Jingui S (2011) Application for diesel engine in fault diagnose based on fuzzy neural network and information fusion. In: 2011 IEEE 3rd international conference on communication software and networks, ICCSN 2011, art. no. 6014398, pp 102–105Google Scholar
  15. 15.
    Galiullin LA (2016) Development of automated test system for diesel engines based on fuzzy logic. In: IEEE 2016 2ND international conference on industrial engineering, Applications And Manufacturing (ICIEAM)Google Scholar
  16. 16.
    Galiullin LA, Valiev RA (2016) Automation of diesel engine test procedure. In: IEEE 2016 2ND international conference on industrial engineering. Applications and Manufacturing (ICIEAM)Google Scholar
  17. 17.
    Galiullin LA, Valiev RA, Mingaleeva LB (2017) Method of internal combustion engines testing on the basis of the graphic language. J Fundam Appl Sci 9SI(1):1524–1533Google Scholar
  18. 18.
    Galiullin LA (2015) Automated test system of internal combustion engines. In: International scientific and technical conference innovative mechanical engineering technologies, equipment and materials-2014, IOP conference series-materials science and engineering, vol 86. pp 012018Google Scholar
  19. 19.
    Valiyev RA, Galiullin LA, Iliukhin AN (2015) Methods of integration and execution of the code of modern programming languages. Int J Soft Comput 10(5):344–347Google Scholar
  20. 20.
    Galiullin LA, Valiev RA (2015) Automated system of engine tests on the basis of Bosch controllers. Int J Appl Eng Res 10(24):44737–44742Google Scholar
  21. 21.
    Li X, Yu F, Jin H, Liu J, Li Z, Zhang X (2011) Simulation platform design for diesel engine fault. In: 2011 International conference on electrical and control engineering, ICECE 2011—Proceedings, art. no. 6057562, pp 4963–4967Google Scholar
  22. 22.
    Valiyev RA, Galiullin LA, Iliukhin AN (2015) Approaches to organization of the software development. Int J Soft Comput 10(5):336–339Google Scholar
  23. 23.
    Valiyev RA, Galiullin LA, Iliukhin AN (2015) Design of the modern domain specific programming languages. Int J Soft Comput 10(5):340–343Google Scholar
  24. 24.
    Biktimirov RL, Valiev RA, Galiullin LA, Zubkov EV, Iljuhin AN (2014) Automated test system of diesel engines based on fuzzy neural network. Res J Appl Sci 9(12):1059–1063Google Scholar
  25. 25.
    Valiev RA, Khairullin AKh, Shibakov VG (2015) Automated design systems for manufacturing processes. Russ Eng Res 35(9):662–665CrossRefGoogle Scholar
  26. 26.
    Yu Y, Yang J (2011) The development of fault diagnosis system for diesel engine based on fuzzy logic. In: Proceedings—2011 8th international conference on fuzzy systems and knowledge discovery, FSKD 2011, 1, art. no. 6019556, pp 472–475Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Naberezhnye Chelny Institute Kazan Federal UniversityKazanRussia

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