Skip to main content
SpringerLink
Log in

Determining Prototypes and Signs for Automated Diagnostics of Steam Turbine Equipment

  • STEAM-TURBINE, GAS-TURBINE, AND COMBINED-CYCLE POWER PLANTS AND THEIR AUXILIARY EQUIPMENT
  • Published:
Thermal Engineering Aims and scope Submit manuscript

Abstract—

Nowadays, turbine building plants try to equip their turbines with automatic control systems that include, in addition to their basic functions, automated fault-diagnosing procedures. The article presents the authors’ experience gained from developing diagnostic systems and evaluating state parameters both for individual components of power equipment and for a power unit and thermal power plant as a whole; in addition, the specific features pertinent to the development of such automated systems are described. Such systems can be used for the purposes of operative and postoperative diagnostics. The first group of applications includes, e.g., vibration diagnostics of turbines, and the second group may include assessing the state of the thermal expansion system components, control system, and turbine plant auxiliary equipment; determining the technical and economic indicators; etc. Development of a prototype is the basis of any diagnostic task. In comparing the equipment’s actual state with the state of the prototype, it is necessary to determine the values of the state parameters from which the diagnostic tasks are solved, i.e., the faults are detected. Diagnostic prototypes' development methods are identified: normative, statistical (expert), physical, and digital. These methods can be combined within a single diagnostic algorithm, due to which it becomes possible to achieve more reliable and efficient (less expensive) assessment of equipment malfunctions during its automatic diagnostics. The advantages and drawbacks of each method are described, and examples of implementing diagnostic tasks with different prototypes are given. Matters concerned with revealing a fault, evaluating the state of equipment components and residual life, and predicting the state parameters are solved. It is shown that one of the complex problems that has to be solved in developing a vibration diagnostic system is to substantiate the relationship between the sign and type of equipment malfunction. Using vibration diagnostics as an example, fault symptoms are grouped into boundary, factor, and correlation ones.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.

Similar content being viewed by others

Notes

  1. This method emerged and has begun to be used only recently owing to a very rapid development of digital systems.

REFERENCES

  1. K. E. Aronson, N. N. Akif’eva, Yu. M. Brodov, T. F. Bogatova, B. E. Murmanskii, and V. V. Kortenko, “The concept of a comprehensive system for monitoring the state of the equipment of a power unit,” Therm. Eng. 49, 137–144 (2002).

    Google Scholar 

  2. V. B. Novoselov, B. E. Murmanskii, and V. V. Lebedev, “Diagnostic of a steam turbine control and protection system at the current stage,” Tyazh. Mashinostr., No. 2, 69–74 (2012).

  3. K. E. Aronson, V. I. Brezgin, Yu. M. Brodov, N. N. Akif’eva, A. S. Rudenko, and D. V. Brezgin, “Information support system for managerial decision-making in the maintenance of thermal power plant equipment,” Elektr. Stn., No. 10, 55–61 (2006).

  4. V. I. Brezgin, K. E. Aronson, I. L. Kozhevnikov, T. V. Panova, and D. V. Brezgin, “Operation (“Ekspluatatsiya” 3.0): Software package,” Programmy EVM. Bazy Dannykh. Tipol. Integr. Mikroskhem: Ofitsial’nyi Byull. Ross. Agentstva Pat. Tovarnym Znakam, No. 1 (46), 12 (2004).

    Google Scholar 

  5. V. I. Brezgin, K. E. Aronson, and T. V. Panova, “Power plant equipment condition monitoring (“KSO 2.x”): Software package,” Programmy EVM. Bazy Dannykh. Tipol. Integr. Mikroskhem: Ofitsial’nyi Byull. Ross. Agentstva Pat. Tovarnym Znakam, No. 1 (46), 13 (2004).

    Google Scholar 

  6. V. I. Brezgin, K. E. Aronson, Yu. M. Brodov, T. V. Panova, and I. L. Kozhevnikov, “Calculation of technical and economic indicators of the power plant (“TEP 2.x”): Software package,” Programmy EVM. Bazy Dannykh. Tipol. Integr. Mikroskhem: Ofitsial’nyi Byull. Ross. Agentstva Pat. Tovarnym Znakam, No. 1 (46), 13 (2004).

    Google Scholar 

  7. SO 153-34.20.501-2003. Rules of Technical Operation of Power Plants and Grids of the Russian Federation (Energoservis, Moscow, 2004).

  8. C. Naylor, Build Your Own Expert System (Sigma, Wilmslow, 1987; Energoatomizdat, Moscow, 1991).

  9. A. Brooking, P. Jones, and F. Kox, Expert Systems: Principles and Case Studies, Ed. by R. M. Forsyth (Chapman and Hall, New York, 1984; Radio i Svyaz’, Moscow, 1987).

  10. K. E. Aronson, Yu. M. Brodov, M. A. Nirenshtein, P. N. Plotnikov, and S. I. Khaet, “Software system for steam turbine unit equipment diagnostics as a whole: Software package,” Programmy EVM. Bazy Dannykh. Tipol. Integr. Mikroskhem: Ofitsial’nyi Byull. Ross. Agentstva Pat. Tovarnym Znakam, No. 1 (46), 30 (2004).

    Google Scholar 

  11. B. E. Murmansky, K. E. Aronson, and Yu. M. Brodov, “An expert system for diagnostics and estimation of steam turbine components condition,” J. Phys.: Conf. Ser. 891, 012279 (2017). https://doi.org/10.1088/1742-6596/891/1/012279

    Article  Google Scholar 

  12. Yu. M. Brodov, K. E. Aronson, Yu. M. Gofman, B. E. Murmanskii, M. A. Nirenshtein, A. Yu. Ryabchikov, and P. N. Plotnikov, Repair and Maintenance of Steam Turbine Unit Equipment: Handbook, Ed. by Yu. M. Brodov, 2nd ed. (Ural’skii Fed. Univ., Ekaterinburg, 2017) [in Russian].

    Google Scholar 

  13. Analysis of the Performance of 150–1200 MW Power Generating Units for 1986–2000 (ORGRES, Moscow) [in Russian].

  14. B. E. Murmanskii, K. E. Aronson, and Yu. M. Brodov, “The effect of damage rate of technological subsystems equipment on functional failures of steam turbines,” Nadezhnost Bezop. Energ. 10, 322–329 (2017).

    Article  Google Scholar 

  15. B. E. Murmanskii, “Development and implementation of the concept of an integrated system for improving the reliability of the condition of a steam turbine unit,” Nadezhnost Bezop. Energ. 28, 44–48 (2015).

    Google Scholar 

  16. A. Y. Sosnovskii, B. E. Murmanskii, Y. M. Brodov, and Y. A. Sakhnin, “Stability of the thermal-expansion system of a steam turbine against external factors,” Power Technol. Eng. 51, 454–458 (2017). https://doi.org/10.1007/s10749-017-0855-3

    Article  Google Scholar 

  17. B. E. Murmanskii, A. Yu. Sosnovskii, and Yu. M. Brodov, “Development of a module for monitoring and diagnosing the state of thermal expansion of steam turbines as part of the state-of-the-art automatic control systems of technological process,” Energetik, No. 4, 51– 53 (2015).

    Google Scholar 

  18. K. E. Aronson, Yu. M. Brodov, A. Yu. Ryabchikov, and M. I. Loginov, “Development of a procedure for substantiating replacement terms for the condenser tubes of steam turbine installations,” Therm. Eng. 60, 567–572 (2013). https://doi.org/10.1134/S0040601513080016

    Article  Google Scholar 

  19. Principal Components in Time Series: The Caterpillar Method, Ed. by D. L. Danilov and A. A. Zhiglyavskii (S.‑Peterb. Gos. Univ., St. Petersburg, 1997) [in Russian].

    Google Scholar 

  20. S. V. Porshnev, K. E. Aronson, and I. V. Solomakha, “Application of the SSA method for the analysis of technological information collected by the thermal power plant information complex,” Izv. Tomsk. Politekh. Inst., Upr., Vychisl. Tekh. Inf. 313 (5), 161–168 (2008).

    Google Scholar 

  21. S. I. Khaet, K. E. Aronson, Yu. M. Brodov, and A. G. Shempelev, “The development and approbation of elements of a system for monitoring and diagnosing the condition of a condenser of a steam turbine,” Therm. Eng. 50, 594–597 (2003).

    Google Scholar 

  22. http://zaorotec.ru/content/centr_monitoringa_oborudovaniya/

  23. V. M. Bobrov, A. A. Vasil’ev, E. E. Goverdovskii, V. M. Kalinichev, P. A. Lepaev, V. K. Pauli, A. N. Sergeev, and A. A. Shcheptev, RD 153-34.0-20.585-00. Guidelines for the Analysis of the Quality of Start-up (Shutdown) of the Principal Heat and Power Equipment of Thermal Power Plants (ORGRES, Moscow, 2000).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Ural Federal University, 620002, Yekaterinburg, Russia

    K. E. Aronson, Yu. M. Brodov, V. B. Novoselov & I. B. Murmanskii

  2. PAO T Plus, 620219, Yekaterinburg, Russia

    B. E. Murmansky

  3. Management Company Teploenergoservis, 620014, Yekaterinburg, Russia

    A. Yu. Sosnovsky

Authors
  1. K. E. Aronson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. E. Murmansky
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yu. M. Brodov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. V. B. Novoselov
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A. Yu. Sosnovsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. I. B. Murmanskii
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. E. Aronson.

Additional information

Translated by V. Filatov

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aronson, K.E., Murmansky, B.E., Brodov, Y.M. et al. Determining Prototypes and Signs for Automated Diagnostics of Steam Turbine Equipment. Therm. Eng. 67, 647–654 (2020). https://doi.org/10.1134/S0040601520090025

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0040601520090025

Keywords:

Search

Navigation