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Principles of Construction of Systems for Diagnosing the Energy Equipment

  • Vitalii P. BabakEmail author
  • Serhii V. Babak
  • Mykhailo V. Myslovych
  • Artur O. Zaporozhets
  • Valeriy M. Zvaritch
Chapter
  • 11 Downloads
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 281)

Abstract

The generalized principles of building information-measuring systems (IMS) designed to measure diagnostic signals of different physical nature (vibrational, acoustic, acoustic emission, thermal, electrical, etc.) that arise in operating electric power equipment are considered. The main diagnostic parameters that can be used as diagnostic features to determine the technical condition of various units of electric power equipment are analyzed. The main components that form the information support of the IMS of diagnostics of electric power equipment are considered.

Keywords

Electric power equipment Diagnostic signal Information-measuring system 

References

  1. 1.
    Babak, S.V., Myslovych, M.V., Sysak, R.M.: Statistical diagnostics of electrical equipment (2015). ISBN 978-966-02-7704-5Google Scholar
  2. 2.
    Babak, V.P.: Hardware-software for monitoring the objects of generation, transportation and consumption of thermal energy (2016). ISBN 978-966-02-7967-4Google Scholar
  3. 3.
    Zaporozhets, A.A., Eremenko, V.S., Serhiienko, R.V., Ivanov, S.A.: Development of an intelligent system for diagnosing the technical condition of the heat power equipment. In: IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), pp. 48–51 (2018).  https://doi.org/10.1109/stc-csit.2018.8526742
  4. 4.
    Zaporozhets, A., Eremenko, V., Isaenko, V., Babikova, K.: Approach for creating reference signals for detecting defects in diagnosing of composite materials. In: Shakhovska, N., Medykovskyy, M. (eds.) Advances in Intelligent Systems and Computing IV. Springer, Cham, vol. 1080, pp. 154–172 (2020).  https://doi.org/10.1007/978-3-030-33695-0_12
  5. 5.
    Czichos, H.: Handbook of Technical Diagnostics. Fundamentals and Application to Structures and Systems (2013). ISBN 978-3-642-25850-3Google Scholar
  6. 6.
    Babak, V.P.: Information support for monitoring of thermal power facilities (2015). ISBN 978-966-02-7478-5Google Scholar
  7. 7.
    Stognii, B., Kyrylenko, O., Butkevych, O., Sopel, M.: Information support of problems of electric power systems control. Energy Econ. Technol. Ecol. 1(30), 13–22 (2012)Google Scholar
  8. 8.
    Edwards, S., Lees, A.W., Friswell, M.I.: Fault diagnosis of rotating machinery. Shock. Vib. Dig. 1(30), 4–13 (1998)CrossRefGoogle Scholar
  9. 9.
    Zaporozhets, A., Eremenko, V., Serhiienko, R., Ivanov, S.: Methods and hardware for diagnosing thermal power equipment based on smart grid technology. In: Shakhovska, N., Medykovskyy, M. (eds.) Advances in Intelligent Systems and Computing III. Springer, Cham, vol. 871, pp. 476–489 (2019).  https://doi.org/10.1007/978-3-030-01069-0_34
  10. 10.
    Zaporozhets, A.: analysis of control system of fuel combustion in boilers with oxygen sensor. Period. Polytech. Mech. Eng. 64(4), 241–248 (2019).  https://doi.org/10.3311/PPme.12572
  11. 11.
    Napolitano, A.: Generalizations of Cyclostationary Signal Processing: Spectral Analysis and Applications (2012). ISBN 9781119973355Google Scholar
  12. 12.
    Yatsuk, V., Mykyizhuk, M., Bubela, T.: Ensuring the measurement efficiency in dispersed measuring systems for energy objects. In: Królczyk, G., Wzorek, M., Król, A., Kochan, O., Su, J., Kacprzyk, J. (eds.) Sustainable Production: Novel Trends in Energy, Environment and Material Systems. Studies in Systems, Decision and Control, vol. 198, pp. 131–149 (2020).  https://doi.org/10.1007/978-3-030-11274-5_9
  13. 13.
    Chen, P., Taniguchi, M., Toyota, T., He, Z.: Fault diagnosis method for machinery in unsteady operating condition by instantaneous power spectrum and genetic programming. Mech. Syst. Signal Process. 1(19), 175–194 (2005).  https://doi.org/10.1016/j.ymssp.2003.11.004CrossRefGoogle Scholar
  14. 14.
    Brie, D.: Modelling of the spalled rolling element bearing vibration signal: an overview and some new results. Mech. Syst. Signal Process. 3(14), 353–369 (2000).  https://doi.org/10.1006/mssp.1999.1237CrossRefGoogle Scholar
  15. 15.
    McCormick, A.C., Nandi, A.K.: Cyclostationarity in rotating machine vibrations. Mech. Syst. Signal Process. 2(12), 225–242 (1998).  https://doi.org/10.1006/mssp.1997.0148CrossRefGoogle Scholar
  16. 16.
    Williams Jr., J.H., DeLonga, D.M., Lee, S.S.: Correlations of acoustic emission with fracture mechanics parameters in structural bridge steels during fatigue. Mat. Eval. 40(10), 1184–1189 (1982)Google Scholar
  17. 17.
    Krishnakumari, A., Elayaperumal, A., Saravanan, M., Arvindan, C.: Fault diagnostics of spur gear using decision tree and fuzzy classifier. Int. J. Adv. Manuf. Technol. 9–12(89), 3487–3494 (2017).  https://doi.org/10.1007/s00170-016-9307-8CrossRefGoogle Scholar
  18. 18.
    Babak, S., Babak, V., Zaporozhets, A., Sverdlova, A.: Method of statistical spline functions for solving problems of data approximation and prediction of object state. In: CEUR Workshop Proceedings, vol. 2353, pp. 810–821 (2019) (Online). http://ceur-ws.org/Vol-2353/paper64.pdf
  19. 19.
    Domanski, P.D.: Statistical measures. In: Control Performance Assessment: Theoretical Analyses and Industrial Practice. Studies in Systems, Decision and Control, vol. 245, pp. 53–74 (2020).  https://doi.org/10.1007/978-3-030-23593-2_4

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Vitalii P. Babak
    • 1
    Email author
  • Serhii V. Babak
    • 2
  • Mykhailo V. Myslovych
    • 3
  • Artur O. Zaporozhets
    • 4
  • Valeriy M. Zvaritch
    • 5
  1. 1.Institute of Engineering Thermophysics of NAS of UkraineKyivUkraine
  2. 2.Committee on Education, Science and Innovation of Verkhovna Rada of UkraineKyivUkraine
  3. 3.Department of Theoretical Electrical EngineeringInstitute of Electrodynamics of NAS of UkraineKyivUkraine
  4. 4.Department of Monitoring and Optimization of Thermophysical ProcessesInstitute of Engineering Thermophysics of NAS of UkraineKyivUkraine
  5. 5.Department of Theoretical Electrical EngineeringInstitute of Electrodynamics of NAS of UkraineKyivUkraine

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