Algorithms of digital information analysis for optimizing checkup of control systems

Information and measuring and control systems


Busurin V. I.1*, Mevedev V. M.2, Karabitsky A. S.3**, Groppa D. V.2***

1. ,
2. State Research Institute Engineeringpace University, 125, prospekt Mira, Moscow, 129226, Russia
3. Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia



The basis of technical support for information, measurement and control systems consists of electronic devices and systems for communicating, gathering, processing, transmission and display of information, which, in stages of development and production, are subjects to diagnosis.

For means of checkup and most of other types of control system tests, it is common to use checkout equipment (CE). The CE hardware and software are developed individually for the needs of specific tests of inertial control system. To simplify the design and improve versatility, this article offers to rethink the software design methodology for CE, allowing forming CE software automatically for control and diagnostics purposes of several similar inertial control systems. This solution will significantly reduce the time and cost of developing hardware and software parts of the CE.

Forming of the software is performed by attaching additional software modules (ASM), which are responsible for unique to a particular inertial control system (ICS) equipment or functionality, to basic software module (BSM). Designed software remains unchanged while being used for control and diagnosis of various ICS’s. BSM performs such functions as distributing software threads and their priorities, ASM launching and control. ASM are developed in conjunction with CE and have unique features. Interaction between the modules is performed by means of shared memory and communication protocols between modules. To sel ect ASM’s necessary to complete the specific test job, the software should analyze digital data, incoming fr om the control system. This data-analyzing algorithm is separated into several major steps: searching for keywords employing reference list, comparing reference lists and detection of ‘answer’ keywords.


checkout equipment, modular system, software, inertial control system, control and diagnosis


  1. Busurin V.I., Medvedev V.M., Karabitskii A.S. Trudy MAI, 2017, no. 92, available at:

  2. Interfeis magistral’nyi posledovatel’nyi elektronnykh modulei. GOST R 52070-2003 (Interface is a bus-structured serial electronic modules. GOST 52070-2003), Moscow, Izd-vo standartov, 2003, 23 p.

  3. Gamma E., Khelm R., Dzhonson R., Vlissides Dzh. Priemy ob"ektno-orientirovannogo proektirovaniya. Patterny proektirovaniya (Design Patterns Elements of Reusable Object-Oriented Software), Saint Petersburg, Piter, 2007, 366 p.

  4. Braude E.J. Tekhnologiya razrabotki programmnogo obespecheniya (Software Engineering. An Object-Oriented Perspective, Saint Petersburg, Piter, 2004, 659 p.

  5. B’yarne Straustrup. Programmirovanie: printsipy i praktika ispol’zovaniya C++ (Programming: Principles and Practice Using C++), Moscow, Vil’yams, 2011, 1248 p.

  6. Bendzhamin C. Pirs. Tipy v yazykakh programmirovaniya (Types and Programming Languages), Moscow, Dobrosvet, 2012, 680 p.

  7. Ian Grekhem. Ob"ektno-orientirovannye metody. Printsipy i praktika (Object-Oriented Methods: Principles & Practice Third Edition), Moscow, Vil’yams, 2004, 880 p.

  8. Kulikov A.M. Trudy MAI, 2015, no. 80, available at: 

  9. Pavlov P.V., Popov F.N. Trudy MAI, 2017, no. 92, available at:

  10. Cherkesov G.N. Nadezhnost’ apparatno-programmnykh kompleksov (Reliability of hardware-software complexes), Saint Petersburg, Piter, 2005, 479 p.

  11. Volkova V.N., Denisov A.A. Osnovy teorii sistem i sistemnogo analiza (Fundamentals of the system theory and system analysis), Saint Petersburg, SPbGPU, 2003, 520 p.

  12. Evlanov L.G. Kontrol’ dinamicheskikh system (Control of dynamic systems), Moscow, Nauka, 1979, 431 p.

  13. Sakhabetdinov I.U. Pribory i sistemy. Upravlenie, kontrol’, diagnostika, 2012, no. 11, pp. 35 – 40.

  14. Alekseev A.A., Solodovnikov A.I., Yakovlev V.B. Diagnostika v tekhnicheskikh sistemakh upravleniya (Diagnostics in technical control systems), Saint Petersburg, Politekhnika, 1997, 188 p.

  15. Tekhnicheskaya diagnostika. Pokazateli diagnostirovaniya. GOST 23664-79. (Technical diagnostics. Indicators of diagnosis. GOST 23664-79), Moscow, Standarty, 1979, 16 p.

  16. Abramov O.V., Rozenbaum A.N. Prognozirovanie sostoyaniya tekhnicheskikh system (Technical systems state prediction), Moscow, Nauka, 1990, 126 p.

  17. Grudinin V.S. Informatsionnye i upravlyayushchie sistemy v tekhnike (Information and control systems in technics), Kirov, Firma Poleks, 2008, 136 p.

  18. Gustav Ollson, Dzhanguido Piani. Tsifrovye sistemy avtomatizatsii i upravleniya (Digital automation and control systems), Saint Petersburg, Nevskii Dialekt, 2001, 557 p.

  19. Wu X., Chen J., Wang W., Zhou Y. Multi-index fusion based fault diagnosis theories and methods, Mechanical Systems and Signal Processing. 2001, no. 15 (5), pp. 995 – 1006.

  20. Chow E.Y., Willsky A.S. Analytical redundancy and the design of robust failure detection systems, IEEE Transactions on Automatic Control, 1984, no. 29 (7), p. 603 – 614.

Download — informational site MAI

Copyright © 2000-2021 by MAI