Methodological basis for measuring expert systems automation of motor and tractor Engines

The paper considers issues of increasing the efficiency of application of measuring expert systems (MES) that solve the problem of reducing power losses of motor and tractor internal combustion engines (ICE) in production conditions due to changes in their technical condition. MES carry out operational control of the energy parameters of the machine and tractor fleet for taking timely repair and maintenance actions. A methodological approach is proposed for creating an automation system for the development of MES, which increases the efficiency of the formation of MES due to the existing expertise in this subject area. The methodological basis of research is a dynamic method for diagnosing ICE. This method uses a test dynamic effect on ICE, which is the most practical for assessing the state of tractor ICE in production conditions, as well as computer modeling of the ICE work processes in order to find informative diagnostic indicators characterizing energy parameters. On the basis of the proposed target function, the software was determined in the form of the model describing a variety of system elements, their features and states, as well as links between them. Information provision was organized, carrying out the functions of collecting, processing and providing information upon request. A method for constructing a logical scheme of the development algorithm MES was formed, which formalizes the process of solving interrelated problems in the synthesis of various structures of hardware and software based on a set of mathematical models. On the example of modeling an ICE unit – a working machine, the effect of varying the input parameters of the model was estimated: torque effects and resistance moments on the diagnostic parameters of the technical state – angular velocities and accelerations. The use of computer modeling of ICE working processes using this methodological approach made it possible to create a digital technology and a measuring system for automated energy monitoring of the tractor fleet of an agricultural enterprise. The computer structural diagrams of ICE and MES models can be used in diagnostic complexes. This will make it possible to increase the accuracy and reliability of determining the state of the internal combustion engine and the mechanisms and working machines aggregated with it, as well as improve the quality of the work they perform.

internal combustion engine, power, dynamic method of diagnostics, modeling of working processes, digital technologists

1. Solov’ev R.Yu., Goryachev S.A. Resource saving in the technical maintenance of agricultural machinery. Sel’skokhozyaistvennye mashiny i tekhnologii = Agricultural Machinery and Technologies, 2013, no. 2, pp. 37–49. (In Russian).

2. Nemtsev A.E., Korotkikh V.V. Methodology for the formation of the system for ensuring the operability of agricultural machinery. Novosibirsk: SFNTsA RAN = Novosibirsk: SFSCA RAS, 2018, 208 p. (In Russian).

3. Kalachin S.V. Prediction of changes in the monitored operational parameters of the machine and tractor aggregates. Traktory i sel’khozmashiny = Tractors and agricultural machinery, 2013, no. 6, pp. 29–31. (In Russian).

4. Chernoivanov V.I., Gabitov I.I., Negovora A.V. Digital technologies and electronic means in the system of technical maintenance and repair of tractor and combine harvesters. Tekhnicheskii servis mashin = Machinery Technical Service, 2018, no. 130, pp. 74–81. (In Russian).

5. Timonin S.B., Timonina A.S. The introduction of digital technologies in the processes of ensuring the optimal functioning of the machinetractor unit. Niva Povolzh’ya = Niva Povolzhya, 2018, no. 3, pp. 124–132. (In Russian).

6. Golubev I.G., Mishurov N.P., Gol’tyapin V.Ya., Apatenko A.S., Sevryugina N.S. and monitoring systems for agricultural machinery. M.: Rosinformagrotekh Publ., 2020, 76 p. (In Russian).

7. Golovin S.I., Revyakin M.M., Zhosan A.A. On the issue of monitoring and managing the technical condition of mobile energy means. Agrotekhnika i energoobespechenie = Agricultural machinery and energy supply, 2019, no. 3 (24), pp. 111–116. (In Russian).

8. Dobrolyubov I.P., Savchenko O.F., Al’t V.V. Identification of the state of agricultural objects by measuring expert systems. Novosibirsk: SO RASKhN = Novosibirsk: SB RAS, 2003, 209 p. (In Russian).

9. Savchenko O.F., Dobrolyubov I.P., Al’t V.V., Ol’shevskii S.N. Automated technological complexes for engine examination. Novosibirsk: SO RASKhN = Novosibirsk: SB RAS, 2006, 272 p. (In Russian).

10. Al’t V.V., Dobrolyubov I.P., Savchenko O.F., Ol’shevskii S.N. Technical support of measuring expert systems of machines and mechanisms in the agro-industrial complex. Novosibirsk: SO RASKhN = Novosibirsk: SB RAS, 2013, 523 p. (In Russian).

11. John de S. Coutinho Advanced Systems Development Management. New York: Wiley, 1977. 433 s.

12. Sistemy avtomatizirovannogo proektirovaniya. Per. s angl. Pod red. Dzh. Allana [Automated design systems. Translated from English. Edited by J. Allan.]. M.: Nauka Publ., 1985, 376 p. (In Russian).

13. Dobrolyubov I.P. Accuracy and information indicators of the measuring channels of the engine expert system. Izmeritel’naya tekhnika = Measuring Techniques, 2011, no. 6, pp. 43–47. (In Russian).

14. Dobrolyubov I.P., Savchenko O.F., Ol’shevskii S.N. Optimization of detection and measurement of ICE parameters by a measuring expert system. Polzunovskii vestnik = Polzunovsky vestnik, 2011, no. 2/2, pp. 275–279. (In Russian).

15. Dobrolyubov I.P., Savchenko O.F., Al’t V.V., Ol’shevskii S.N., Klimenko D.N. Modeling the process of optimal determination for the parameters of the condition of internal combustion engine by a measurement expert system. Vychislitel’nye tekhnologii = Computational technologies, 2015, vol. 20, no. 6, pp. 22–35. (In Russian).

16. Savchenko O.F., Al’t V.V., Dobrolyubov I.P., Ol’shevskii S.N. Instrumentation and means of automatic combustion analysis for diesel engines test facilities. Dvigatelestroenie = Engines construction, 2014, no. 2, pp. 26–31. (In Russian).

17. Al’t V.V., Savchenko O.F., Ol’shevskii S.N., Elkin O.V., Klimenko D.N. Automated technology of energy monitoring of the tractor fleet of an agricultural enterprise. Trudy GOSNITI = Proceedings of GOSNITI, 2017, vol. 129, pp. 36–44. (In Russian).

18. Al’t V.V., Savchenko O.F., Elkin O.V. Digital technology of assessment the power capacity of tractor fleet of an agricultural enterprise. Sel’skokhozyaistvennye mashiny i tekhnologii = Agricultural Machinery and Technologies, 2019, vol. 13, no. 4, pp. 25–31. (In Russian). DOI 10.22314/2073-7599-2019-13-4-25-31.