Optimization of identifying the technical state of gas compressor units using entropy estimates

Authors

  • Михайло Іванович Горбійчук Ivano-Frankivsk National Technical University of Oil and Gas Carpatska, 15, Ivano-Frankivsk, Ukraine, 76018, Ukraine https://orcid.org/0000-0002-2758-1381
  • Мар’ян Остапович Слабінога Ivano-Frankivsk National Technical University of Oil and Gas Carpatska, 15, Ivano-Frankivsk, Ukraine, 76018, Ukraine https://orcid.org/0000-0002-7296-0356

DOI:

https://doi.org/10.15587/1729-4061.2014.20684

Keywords:

diagnostic process, entropy estimates, technical condition, diagnostic value, functional module

Abstract

The paper is devoted to the problem of optimizing the identification process of compressor units using entropy estimates. The developments in the identification of technical states and diagnosis of malfunctions are examined in the paper, the theoretical foundations of the concept of diagnostic value and its application in other industries are described as well.

The feasibility of using the methods, which use a diagnostic value for optimizing the process of identifying technical states of gas compressor units, was proved. The concept of the software developed for studying the subject matter as a functional module was given, the process of algorithm performance was considered. The results of algorithm performance with real diagnostic data were obtained and analyzed.

The conclusion about the applicability of the diagnostic value methods for optimizing the diagnostic process of technical malfunctions and the technical evaluation of gas compressor units, was made

Author Biographies

Михайло Іванович Горбійчук, Ivano-Frankivsk National Technical University of Oil and Gas Carpatska, 15, Ivano-Frankivsk, Ukraine, 76018

Professor

Computer Systems and Networks Department

Мар’ян Остапович Слабінога, Ivano-Frankivsk National Technical University of Oil and Gas Carpatska, 15, Ivano-Frankivsk, Ukraine, 76018

Post-Graduate student

Computer Systems and Networks Department

References

  1. Cheeseman, Р. On The Relationship between Bayesian and Maximum Entropy Inference [Text] / P. Cheeseman , J. Stutz. – AIP Conf. Proc. 735, 2004. – P. 443-460.
  2. Соколов, В. А. Построение решения для оценки технического состояния конструктивных систем зданий и сооружений с использованием вероятностных методов распознавания [Текст] / В. A. Соколов // Инженерно-строительный журнал. – 2010. – №6(16). – С. 48-57.
  3. Chang, T. Vibration Fault Diagnosis of Rotating Machine Based on the Principle of Entropy Increase [Text] / T. Chang //Advanced Materials Research. – 2012. – Vol. 530. – P. 109-114.
  4. Сухов, A. В. Оптимальное управление техническим состоянием производственных объектов в информационном пространстве с использованием энтропии покрытия [Текст] / А. Сухов, М. Гатилов, М. Зайцев // Компрессорная техника и пневматика. – 2010. – №4. – С. 60-78.
  5. Чилин, С. А. Газоперекачивающий агрегат как объект диагностирования: Учебно-методическое пособие [Текст]/С. Чилин, Ю. Божков – М.:Газпром, 2004. – 136 с. – СНО 04.10.02.028.01.
  6. Биргер, И.А. Техническая диагностика [Текст] / И. Биргер – М:Машиностроение, 1978. - 240 с.
  7. Hughes, J.M. Real World Instrumentation with Python [Текст]/ John M. Hughes. – Sebastopol: O’Reilly Media, Inc., 2010. – 622 c.
  8. McKinney, W. Python for Data Analysis [Текст] / Wes McKinney. – Sebastopol: O’Reilly Media, Inc., 2012. – 470 c.
  9. Downey, A. Think Python [Текст] / Allen Downey. – Sebastopol: O’Reilly Media, Inc., 2012. – 300 c.
  10. Дьяконов, В. MATLAB. Обработка сигналов и изображений: Специальный справочник [Текст]/ В. Дьяконов – Пб.:Питер, 2002. – 608 с.
  11. Cheeseman, Р. (2004). On The Relationship between Bayesian and Maximum Entropy Inference. AIP Conf. Proc. 735, 443-460.
  12. Sokolov, V. A. (2010). Building solutions for the technical condition assessment of structural systems of buildings and structures using probabilistic methods of recognition. Construction Engineering Journal, 6(16), 48-57.
  13. Chang, T. (2012). Vibration Fault Diagnosis of Rotating Machine Based on the Principle of Entropy Increase, Advanced Materials Research, 530, 109-114.
  14. Sukhov, A. V. (2010). Optimal control of a technical condition of production facilities in the information space using the covering entropy. Compressors and Pneumatics, 4, 60-78.
  15. Chilin, S. A. (2004). Gas compressor unit as the diagnostics object. Moscow, Russia: Gazprom, 130.
  16. Birger, I. A. (1978). Technical Diagnostics. Moscow, USSR: Mechanical engineering, 240.
  17. Hughes, J. M. (2010). Real World Instrumentation with Python. Sebastopol, USA: O’Reilly, 622.
  18. McKinney, W. (2012). Python for Data Analysis. Sebastopol, USA: O’Reilly, 470.
  19. Downey, A. (2012). Think Python. Sebastopol, USA: O’Reilly, 300.
  20. Dyakonov, V. (2002). Matlab: Signal and image processing. Sankt-Peterburg, Russia: Piter, 608.

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Published

2014-02-14

How to Cite

Горбійчук, М. І., & Слабінога, М. О. (2014). Optimization of identifying the technical state of gas compressor units using entropy estimates. Eastern-European Journal of Enterprise Technologies, 1(3(67), 8–11. https://doi.org/10.15587/1729-4061.2014.20684

Issue

Vol. 1 No. 3(67) (2014): Control processes

Section

Control processes

License

Copyright (c) 2014 Михайло Іванович Горбійчук, Мар’ян Остапович Слабінога

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