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Experimental Study on Vibration Analysis of Rotor–Stator Rub Defect in a Gas Turbine Generator Set

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Abstract

Monitoring turbomachines requires the pre-selection of several indicators used to process vibration signals. In this study, spectral analysis and orbital analysis were used to identify the nature of faults in a gas turbine generator set used to produce electricity. Using international vibration standards ISO 10816-4 and ISO 7919-4, vibration trend measurements, spectral analysis, and orbit analysis, it is possible to detect the severity of malfunctions and determine their nature, including unbalance, misalignment, rubbing, rotor bow, mechanical looseness, and shaft crack. According to this case study, the generator had a thermal imbalance which caused the rotor to bend, creating a complete annular rub between the shaft end cover and the fan of the excitation unit. Diagnostic features obtained by fast Fourier transform (FFT) related to mechanical imbalance have been explained. Also, orbit plots were effectively used to explain the unique nature of the fault.

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References

  1. M. Akhtar, M.S. Kamran, N. Hayat et al., High-vibration diagnosis of gas turbines: an experimental investigation. J. Vib. Control. 27, 3–17 (2021)

    Article  Google Scholar 

  2. Almasi AJCE. (2012) Gas Turbine Engineering Handbook. 119: 7-8.

  3. N. Bachschmid, P. Pennacchi, A. Vania et al., Diagnostic significance of orbit shape analysis and its application to improve machine fault detection. J. Braz. Soc. Mech. Sci. Eng. 26, 200–208 (2004)

    Article  Google Scholar 

  4. D.E. Bently, C.T. Hatch, B. Grissom, Fundamentals of Rotating Machinery Diagnostics. (ASME Press, London, 2002)

    Google Scholar 

  5. B. Cahyono, D. Priyanta, F.R.F.J.I.J.O.M.E.I. Ramadhan et al., Vibration spectrum analysis for indicating damage on turbine and steam generator amurang unit 1. Int. J. Marine Eng. Innov. Res. (2017). https://doi.org/10.12962/j25481479.v2i1.2688

    Article  Google Scholar 

  6. C. Da Costa, R.S. Da Gama, C.E. Nascimento et al., Orbit analysis for imbalance fault detection in rotating machinery. IOSR J. Electr. Electron. Eng. 13, 43–53 (2018)

    Google Scholar 

  7. A. Davies, Handbook of Condition Monitoring: Techniques and Methodology. (Springer, Netherlands, 1998)

    Book  Google Scholar 

  8. A.J.W. Dimarogonas, A study of the Newkirk effect in turbomachinery. Wear. 28, 369–382 (1974)

    Article  Google Scholar 

  9. M. Hamadache, D. Lee, E. Mucchi et al., Vibration-based bearing fault detection and diagnosis via image recognition technique under constant and variable speed conditions. Appl. Sci. 8, 1392 (2018)

    Article  Google Scholar 

  10. V. Hariharan, P. Srinivasan, Vibration analysis of parallel misaligned shaft with ball bearing system. Sonklanakarin J. Sci. Technol. 33, 61 (2011)

    Google Scholar 

  11. V. Hariharan, P. Srinivasan, Vibrational analysis of flexible coupling by considering unbalance. World Appl. Sci. J. 8, 1022–1031 (2010)

    Google Scholar 

  12. A. Hidayat, I. Firmansyah and U. Wasiwitono (2021) Analysis of Muara Tawar CCPP Block 1 Steam Turbine Vibration. In IOP Conference Series: Materials Science and Engineering. IOP Publishing, p. 012117

  13. H. Jeong, S. Park, S. Woo et al., Rotating machinery diagnostics using deep learning on orbit plot images. Procedia Manuf. 5, 1107–1118 (2016)

    Article  Google Scholar 

  14. H. Ma, Q. Zhao, X. Zhao et al., Dynamic characteristics analysis of a rotor–stator system under different rubbing forms. Appl. Math. Model. 39, 2392–2408 (2015)

    Article  Google Scholar 

  15. A. Muszynska, Vibrational diagnostics of rotating machinery malfunctions. J. Rotat. Mach. 1, 237–266 (1995)

    Article  Google Scholar 

  16. A.D. Nembhard, J.K. Sinha, A.J.M. Yunusa-Kaltungo, Experimental observations in the shaft orbits of relatively flexible machines with different rotor related faults. Measurement. 75, 320–337 (2015)

    Article  Google Scholar 

  17. A.D. Nembhard, J.K.J.M. Sinha, Comparison of experimental observations in rotating machines with simple mathematical simulations. Measurement. 89, 120–136 (2016)

    Article  Google Scholar 

  18. P. Pennacchi, A. Vania, Analysis of rotor-to-stator rub in a large steam turbogenerator. Int. J. Rotating Mach. (2007). https://doi.org/10.1155/2007/90631

    Article  Google Scholar 

  19. M.B. Reksono, and I.M. Miasa (2019) Vibration analysis for reducing excessive vibration level on gas turbine generator (GTG) 100 MW in cogeneration power plant.in Journal of Physics: Conference Series. IOP Publishing, p. 012083

  20. W.M. Salilew, Z.A.A. Karim, A.T. Baheta, WITHDRAWN Review on Gas Turbine Condition Based Diagnosis Method. (Elsevier, London, 2021)

    Book  Google Scholar 

  21. C. Scheffer, P. Girdhar, Practical Machinery Vibration Analysis And Predictive Maintenance. (Elsevier, London, 2004)

    Google Scholar 

  22. A. Sen, M.C. Majumder, S. Mukhopadhyay et al., Polar and orbit plot analysis for unbalance identification in a rotating system. IOSR J. Mech. Civil Eng. 14, 49–56 (2017)

    Article  Google Scholar 

  23. M. Tahan, E. Tsoutsanis, M. Muhammad et al., Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review. Appl. Energy. 198, 122–144 (2017)

    Article  Google Scholar 

  24. B. Wu, S. Feng, G. Sun et al., Identification method of shaft orbit in rotating machines based on accurate Fourier height functions descriptors. Shock Vib. (2018). https://doi.org/10.1155/2018/3737250

    Article  Google Scholar 

  25. ISO 20816-1:2016. (2016) Mechanical vibration—measurement and evaluation of machine vibration — Part 1: General guidelines

  26. J.J.Yu (2013) Rub diagnostics based on vibration data. Turbo Expo: Power for Land, Sea, and Air. American Society of Mechanical Engineers, V004T006A003.

  27. O.A. Zargar, Turbine compressor vibration analysis and rotor movement evaluation by shaft center line method (The case history related to main turbine compressor of an Olefin plant in Iran oil industries). Int. J. Mech. Mech. Eng. 8, 218–227 (2014)

    Google Scholar 

  28. J. Zhang, W. Ma, J. Lin et al., Fault diagnosis approach for rotating machinery based on dynamic model and computational intelligence. Measurement. 59, 73–87 (2015)

    Article  Google Scholar 

Download references

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Correspondence to Abdelfettah Mehalaine.

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Mehalaine, A., Berkani, O. Experimental Study on Vibration Analysis of Rotor–Stator Rub Defect in a Gas Turbine Generator Set. J Fail. Anal. and Preven. 23, 2305–2314 (2023). https://doi.org/10.1007/s11668-023-01739-z

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