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Concept of computer-aided assessment of the technical condition of operated gas turbine vanes

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article presents a multi-stage algorithm for automatic (without any human, user – diagnostician intervention) detection of vanes-blades (technical objects) and their surfaces on a digital image, combined with color analysis, aimed at determining the technical condition of the tested turbine elements. The images recorded with the use of a camera, containing previously dismantled from the turbine operated stator vanes, were used as the exemplary analysis material. The paper presents the algorithm for the detection of the vanes’ airfoil surfaces with the impact of the applied techniques and methods of image processing and analysis on the final result (software localization of the vane’s trailing and leading edge), Then, the obtained image data, including the structural changes of both the vane’s coating and material (metallographic testing) were correlated with the surface colour scheme (colour segmentation based on the YCbrCr colour space model). Thanks to this approach, areas on the surface of the blade were distinguished, characteristic for proper, overheated and transient condition.
Rocznik
Tom
Strony
104--112
Opis fizyczny
Bibliogr. 24 poz., rys.
Twórcy
autor
  • Bialystok Technical University Wiejska 45, 15–333 Białystok Poland
autor
  • Bialystok Technical University Wiejska 45, 15–333 Białystok Poland
autor
  • Air Force Institute of Technology Księcia Bolesława 5, 01–494 Warszawa Poland
Bibliografia
  • 1. Balicki W., Szczeciński S.: Diagnosing aircraft turbine engines (in Polish). Maszyny wirnikowe. Biblioteka Naukowa Instytutu Lotnictwa. Warszawa 2001.
  • 2. Błachnio J., Bogdan M.: A non-destructive method to assess condition of gas turbine blades based on the analysis of blade surface image. Russian Journal of Nondestructive Testing, 46 (2010), pp. 860–866.
  • 3. Błachnio J., Bogdan M., Kułaszka A.: New non–destructive methods of diagnosing health of gas turbine blades, in: by E. Benini (eds.). Advances in Gas Turbine Technology 2011. InTech, pp. 465–498.
  • 4. Błachnio J., Bogdan M., Zasada D.: Increased temperature impact on durability of gas turbine blades. Eksploatacja i Niezawodnosc – Maintenance and Reliability 19(1) (2017) pp. 48–53.
  • 5. Crostack H. A., Padmapriya N.: NDT of coatings, surface modified layers, and adhesives. Reference Module in Materials Science and Materials Engineering. Elsevier, 2016.
  • 6. Duda R. O., Hart P. E.: Use of the Hough Transformation to detect lines and curves in pictures. ACM, 15 (1972), pp. 11–15.
  • 7. Giampaolo G. T.: Turbine Handbook: Principles and Practice (5th Edition). Lilburn (Georgia): Fairmont Press, 2013.
  • 8. Girtler J., Dzida M.: Operation evaluation method for marine turbine combustion engines in terms of energetics. Polish Maritime Research 23, 4(92) (2016), pp. 67–72.
  • 9. Gonzales R. C, Woods R. E.: Digital Image Processing. 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, (2002).
  • 10. Grządziela A.: Analysis of vibration parameters of ship gas turbine engines. Polish Maritime Research, 2 (2006), pp. 22–26.
  • 11. Korczewski Z.: Endoscopic examination of naval gas turbines. Polish Maritime Research, 4 (1998), pp. 13–16.
  • 12. Korczewski Z.: Exhaust gas temperature measurements in diagnostic examination of naval gas turbine engines. Polish Maritime Research, 18(2) (2011), pp. 37–43.
  • 13. Korczewski Z.: Operational causes of fatigue failures within passages of gas turbine engines. Polish Maritime Research, 17 (2010), pp. 57–61.
  • 14. Lewitowicz J., Kowalski M., Żyluk A.: Modern diagnostics of aircraft gas turbine engines – some selected issues. Journal of KONBiN, 29(1) (2014), pp. 33–40.
  • 15. Matzkanin G.A.: Selecting a nondestructive testing method: visual inspection. Advanced Materials, Manufacturing and Testing Information Analysis Center 1(3) (2006), pp. 7–10.
  • 16. Pitkänen J., Hakkarainen T., Jeskanen H., Kuusinen P., Lahdenperä K., Särkiniemi P., Kemppainen M., Pihkakoski M.: NDT methods for revealing anomalies and defects in gas turbine blades. Proc 15th WCNDT, Rome 43 (2001), pp. 601–604.
  • 17. Poynton C.: A guided tour of color space new foundations for video technology. Proceedings of the SMTPE Advanced Television and Electronic Imaging Conference (1995), pp. 167–180.
  • 18. Raj B., Thavasimuthu M., Jayakumar T.: Practical nondestructive testing, 3rd eds. New Delhi, India: Narosa Publishing House, 2014.
  • 19. Rajendran R., Ganeshachar M.D., Rao T. M., Condition assessment of gas turbine blades and coatings, In: Engineering Failure Analysis, 18 (8) (2011), pp. 2104–2110.
  • 20. Reed R. C.: The Superalloys fundamentals and applications. Cambridge: Cambridge University Press, 2006.
  • 21. Ridler T., Calvard S.: Picture thresholding using an interactive selection method. IEEE Trans. System, Man and Cybernetics, SMC, 8(8) (1978), pp. 630–632.
  • 22. Soares C.: Gas Turbines: A Handbook of Air, Land and Sea Applications (Second Edition), Butterworth-Heinemann, Oxford, 2015.
  • 23. Sujata M., Madan M., Raghavendra K., Venkataswamy M. A., Bhaumik S. K.: Identification of failure mechanisms in nickel base superalloy turbine blades through microstructural study. Engineering Failure Analysis 17(6) (2010), pp. 1436–1446.
  • 24. Tresa M. Nickel-based superalloys for advanced turbine engines: chemistry, microstructure and properties. J. Propuls. Power 22(2) (2006), pp. 361–374.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e9313341-7b63-4a46-a9cf-75a8fd1b48c6
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