APPLICATION OF FUZZY LOGIC METHODS TO AUTOMATE THE PROCESS OF INDUCTION SOLDERING

Дата поступления: 
22.05.2018
Год: 
2018
Номер журнала (Том): 
УДК: 
004.896
DOI: 

10.26731/1813-9108.2018.2(58).45-56

Файл статьи: 
Страницы: 
45
56
Аннотация: 

The article solves the problem of developing an intelligent system for controlling the process of aluminum waveguide paths induction soldering. The authors introduce a concept of a control system, within the framework of which the use of fuzzy logic methods is suggested as a solution. A generalized scheme of an intelligent automated induction soldering system is constructed that forms control based on a mismatch between the temperatures and heating rates of the welded waveguide assemblies, as well as the evaluation of the soldering process control quality on the basis of temperatures and heating rates mismatch. As the output parameters of the intelligent system, the choice of the control algorithm is proposed, as well as the amount of regulator coefficients correction. Based on the results of the expert evaluation, the terms of the input and output variables are composed. The proposed control algorithm is implemented within the framework of the current automated control system for spacecraft’s waveguide soldering. Based on the results of numerical experiments, both the forms of control actions in the system and their parameters were selected. The proposed approach to the formation of control was tested in a series of full-scale experiments on the waveguide paths soldering, as a result of which the heating curves of the product elements were obtained, according to which it is possible to judge the effectiveness of using intelligent control based on a fuzzy regulator. Application of the proposed approach allows ensuring high quality of induction heating process control and obtaining reliable permanent connections of waveguide path elements.

Список цитируемой литературы: 

1.   Sil'chenko S. N., Mikhnev M., Ankudinov A. V., Kudryavtsev I. V. Obespechenie prochnosti i tochnosti shirokopolosnykh volnovodno-raspredelitel'nykh sistem ustroistv kosmicheskoi svyazi [Provision of strength and accuracy of broadband waveguide-distributing systems for space communication devices]. Problemy mashinostroeniya i nadezhnosti mashin [Journal of Machinery Manufacture and Reliability], 2012, No.1, pp. 112-117.

2.   Vologdin V. V., Kushch E. V., Asamov V. V. Induktsionnaya paika [Induction soldering]. Leningrad: Mashinostroenie Publ., 1989.

3.   Slukhotskii A. E. Induktory [Inductors]. Leningrad: Mashinostroenie Publ., 1989.

4.   Slukhotskii A. E., Ryskin S. E. Induktory dlya induktsionnogo nagreva [Inductors for induction heating]. Leningrad:  Energiya Publ., 1974.

5.   Murygin A. V., Tynchenko V. S., Laptenok V. D., Emilova O. A., Bocharov A. N. Complex of automated equipment and tech-nologies for waveguides soldering using induction heating. IOP Conference Series: Materials Science and Engineering, 2017, No.173(1), S. 012023.

6.   Tynchenko V. S., Murygin A. V., Emilova O. A., Bocharov A. N., Laptenok V. D. The automated system for technological pro-cess of spacecraft's waveguide paths soldering. IOP Conference Series: Materials Science and Engineering, 2016, No.155(1), S. 012007.

7.   Tynchenko V. S., Murygin A. V., Petrenko V. E., Seregin Y. N., Emilova O. A. A control algorithm for waveguide path induction soldering with product positioning. IOP Conference Series: Materials Science and Engineering, 2017, No.255(1), S. 012018.

8.   Murygin A. V., Tynchenko V. S., Laptenok V. D., Emilova O. A., Seregin Y. N. Modeling of thermal processes in waveguide tracts induction soldering. IOP Conference Series: Materials Science and Engineering, 2017, No.173(1), S. 012026.

9.   Kudryavtsev I. V., Barykin E. S., Gotselyuk O. B. Matematicheskaya model' nagreva volnovoda pri peredache vysokoi moshchnosti signala [Mathematical model of waveguide heating during transmission of high signal power]. Molodoi uchenyi [Young scientist], 2013, No.9, pp. 52-57.

10. Burakov M. V. Nechetkie kontrollery [Fuzzy controllers]. St. Petersburg: GUAP Publ., 2010.

11. Demidova L., Kirakovskii V. V., Pylkin A. N. Algoritmy i sistemy nechetkogo vyvoda pri reshenii zadach diagnostiki gorodskikh inzhenernykh kommunikatsii v srede MATLAB [Algorithms and systems of fuzzy inference when solving problems of diagnostics of urban engineering communications in MATLAB environment]. Moscow: Radio i svyaz' Publ., 2005.

12. Dudkin Yu. P., Titov Yu. K., Filippenkov R. G., Khizhnyakov Yu. N. Nechetkoe upravlenie chastotoi vrashcheniya svobodnoi turbiny gazoturbinnogo dvigatelya [Fuzzy control of the rotation frequency of a free turbine of a gas turbine engine]. Vestnik Moskovskogo aviatsionnogo instituta [Vestnik Moskovskogo Aviatsionnogo Instituta], 2010, No.17(6), pp. 55-60.

13. Gostev V. I. Fuzzy controllers in automatic control systems [Fuzzy controllers in automatic control systems]. Radioamator, 2008.

14. Minaev Yu. N., Filimonova O. Yu. Benameur Lies. Metody i algoritmy resheniya zadach identifikatsii i prognozirovaniya v usloviyakh neopredelennosti v neirosetevom logicheskom bazise [Methods and algorithms for solving problems of identification and prediction in conditions of uncertainty in a neural network logical basis]. Moscow: Goryachaya liniya-Telekom Publ., 2003.

15. Burakov M. V., Konovalov A. S. Sintez nechetkikh logicheskikh regulyatorov [Synthesis of fuzzy logic regulators]. Informatsionno-upravlyayushchie sistemy [Information and Control Systems], 2011, No. 1, pp. 22-27.

16. Tynchenko V. S., Tynchenko V. V., Bukhtoyarov V. V., Tynchenko S. V., Petrovskyi, E. A. The multi-objective optimization of complex objects neural network models. Indian Journal of Science and Technology, 2016, No.29 (9).

17. Aleksandrov A. G., Palenov M. V. Sostoyanie i perspektivy razvitiya adaptivnykh PID-regulyatorov [The state and prospects of the development of adaptive PID regulators]. Avtomatika i telemekhanika [Automation and Remote Control], 2014, No.2, pp. 16-30.

18. Arsen'ev G. N., Shalygin A. A. Matematicheskoe modelirovanie nechetkikh regulyatorov na osnove MATLAB [Mathematical modeling of fuzzy regulators based on MATLAB]. Informatsionno-izmeritel'nye i upravlyayushchie sistemy [Journal Information-measuring and Control Systems], 2011. No.9 (5), pp. 26-37.

19. Chen H. C. Optimal fuzzy pid controller design of an active magnetic bearing system based on adaptive genetic algorithms. IEEE 2008 International Conference on Machine Learning and Cybernetics. 2008, No.4, S. 2054-2060.

20. Sabir M. M., Ali T. Optimal PID controller design through swarm intelligence algorithms for sun tracking system. Applied Mathematics and Computation, 2016, No. 274, pp. 690-699.