Journal of Mechanical Science and Technology

, Volume 32, Issue 12, pp 5947–5959 | Cite as

Novel performance diagnostic logic for industrial gas turbines in consideration of over-firing

  • Jae Hong Lee
  • Tong Seop KimEmail author


The performance of gas turbine degrades as the operating hours accumulate, and compressor fouling is the dominant factor. Compressor fouling can increase the turbine inlet temperature (i.e., over-firing). The diagnosis of over-firing is important because it affects the performance and lifetime of the turbine. This paper proposes new performance diagnosis logic for gas turbines that considers over-firing. The aim is to eliminate the effects of over-firing due to the compressor fouling. The key feature is analyzing the performance degradation based on modification in the turbine inlet temperature. An in-house code was developed to realize the logic. First, the code was verified through a comparison with a commercial software package, GateCycle 6.1.2, using real operating data of an industrial gas turbine during almost two years. Then, virtual operation data under compressor fouling were generated and used for the validation of the logic. The conventional diagnostic logic could predict the degradation in usual operation but could not evaluate the actual performance degradation correctly in a power control operation where power generation should comply with the power demand. However, the new logic evaluated the exact performance degradation for the entire period analyzed. The results confirm the importance of considering over-firing for exact performance diagnosis.


Compressor fouling Gas turbine Model-based performance diagnosis Over-firing Performance degradation Turbine inlet temperature 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    F. R. P. Arrieta and E. E. S. Lora, Influence of ambient temperature on combined–cycle power–plant performance, Energy, 80 (2005) 261–272.Google Scholar
  2. [2]
    A. De Sa and S. Al Zubaidy, Gas turbine performance at varying ambient temperature, Applied Thermal Engineering, 31 (14–15) (2011) 2735–2739.CrossRefGoogle Scholar
  3. [3]
    A. A. Amell and F. J. Cadavid, Influence of the relative humidity on the air cooling thermal load in gas turbine power plant, Applied Thermal Engineering, 22 (13) (2002) 1529–1533.CrossRefGoogle Scholar
  4. [4]
    E. B. da Silv, M. Assato and R. C. de Lima, Performance prediction of gas turbine under different strategies using low heating value fuel, Proceedings of ASME Turbo Expo, San Antonio, Texas, USA (2013) GT2013–96013.Google Scholar
  5. [5]
    R. Kurz and K. Brun, Degradation in gas turbine systems, Journal of Engineering for Gas turbines and Power, 123 (1) (2001) 70–77.CrossRefGoogle Scholar
  6. [6]
    I. S. Diakunchak, Performance deterioration in industrial gas turbines, Journal of Engineering for Gas Turbines and Power, 114 (2) (1992) 161–168.CrossRefGoogle Scholar
  7. [7]
    J. P. Stalder, Gas turbine compressor washing state of the art: Field experiences, Journal of Engineering for Gas Turbines and Power, 123 (2) (2000) 363–370.CrossRefGoogle Scholar
  8. [8]
    A. Zwebek and P. Pilidis, Degradation effects on combined cycle power plant performance–Part 1: Gas turbine cycle component degradation effects, Journal of Engineering for Gas Turbines and Power, 125 (3) (2003) 651–657.CrossRefGoogle Scholar
  9. [9]
    S. T. Cloyd and A. J. Harris, Gas turbine performance–New application and test correction curves, International Gas Turbine and Aeroengine Congress and Exposition, Houston, Texas, USA (1995) 95–GT–167.Google Scholar
  10. [10]
    C. B. Meher–Homji, A. B. Focke and M. B. Wooldridge, Fouling of axial flow compressors–cause, effects, detection, and control, Proceeding of the Eighteenth Turbomachinery Symposium, Texas, USA (1989) T1855–76.Google Scholar
  11. [11]
    Z. S. Vanini, N. Meskin and K. Khorasani, Mutiple–model sensor and components fault diagnosis in gas turbine engines using autoassociative neural networks, Journal of Engineering for Gas Turbines and Power, 136 (9) (2014) 091603–1–091603–16.CrossRefGoogle Scholar
  12. [12]
    S. S. Tayarani–Bathaie and K. Khorasani, Fault detection and isolation of gas turbine engines using a bank of neural networks, Journal of Process Control, 36 (2015) 22–41.CrossRefGoogle Scholar
  13. [13]
    L. A. Urban, Gas path analysis applied to turbine engine condition monitoring, Journal of Aircraft, 10 (7) (1973) 400–406.CrossRefGoogle Scholar
  14. [14]
    D. L. Doel, TEMPER–A gas–path analysis tool for commercial jet engines, Journal of Engineering for Gas Turbines and Power, 116 (1) (1994) 82–89.CrossRefGoogle Scholar
  15. [15]
    A. Stamatis, K. Mathioudakis, M. Smith and K. Papailou, Gas turbine component fault identification by means of adaptive performance modeling, International Gas Turbine and Aeroengine Congress and Exposition, Brussels, Belgium (1990) 90–GT–376.Google Scholar
  16. [16]
    P. C. Escher, Gas turbine data validation using gas path analysis, Proceedings of ASME Turbo Expo, Amsterdam, The Netherlands (2002) GT2002–30024.Google Scholar
  17. [17]
    Y. G. Li, Gas turbine performance and health status estimation using adaptive gas path analysis, Journal of Engineering for Gas Turbines and Power, 132 (4) (2010) 041701–1–041701–9.CrossRefGoogle Scholar
  18. [18]
    D. W. Kang and T. S. Kim, Model–based performance diagnostics of heavy–duty gas turbines using compressor map adaptation, Applied Energy, 212 (2018) 1345–1359.CrossRefGoogle Scholar
  19. [19]
    E. Tsoutsanis, N. Meskin, M. Benammar and K. Khorasani, A component map tuning method for performance prediction and diagnostics of gas turbine compressors, Applied Energy, 135 (2014) 572–585.CrossRefGoogle Scholar
  20. [20]
    E. Tsoutsanis, N. Meskin, M. Benammar and K. Khorasani, A dynamic prognosis scheme for flexible operation of gas turbines, Applied Energy, 164 (2016) 686–701.CrossRefGoogle Scholar
  21. [21]
    A. Ajami and M. Daneshvar, Data driven approach for fault detection and diagnosis of turbine in thermal power plant using independent component analysis (ICA), Electrical Power and Energy Systems, 43 (1) (2012) 728–735.CrossRefGoogle Scholar
  22. [22]
    J. H. Lee, T. S. Kim and E. Kim, Prediction of power generation capacity of a gas turbine combined cycle cogeneration plant, Energy, 124 (2017) 187–197.CrossRefGoogle Scholar
  23. [23]
    D. W. Kang, A study on improvements in gas turbine system design, operation strategy and performance diagnostic for power plant performance enhancement, Ph.D. Thesis, Inha University, Korea (2015).Google Scholar
  24. [24]
    ASME performance test codes on gas turbines, American Society of Mechanical Engineers (2005): PTC 22–2005.Google Scholar
  25. [25]
    MathWorks, MATLAB R2016a (2016).Google Scholar
  26. [26]
    R. R. Gay, C. A. Palmer and M. R. Erbes, Power plant performance monitoring, First Ed., Tech Books International, India (2006).Google Scholar
  27. [27]
    B. J. McBride, M. J. Zehe and S. Gordon, NASA Glenn coefficient for calculating thermodynamic properties of individual species, Glenn Research Center (2002) Report No.: NASA/TP–2002–211556.Google Scholar
  28. [28]
    P. P. Walsh and P. Fletcher, Gas turbine performance, Second Ed., Blackwell Science, Oxford, UK (2004).CrossRefGoogle Scholar
  29. [29]
    M. J. Moran, H. N. Shapiro, D. D. Boettner and M. B. Bailey, Principles of engineering thermodynamics, Seventh Ed., John Wiley & Sons, New Jersey, USA (2012).Google Scholar
  30. [30]
    GE Energy, GateCycle 6.1.2 (2015).Google Scholar
  31. [31]
    S. R. Turns, An introduction to combustion concept and applications, Second Ed., McGraw–Hill, New York, USA (2000).Google Scholar
  32. [32]
    J. J. Lee, D. W. Kang and T. S. Kim, Development of a gas turbine performance analysis program and its application, Energy, 36 (8) (2011) 5274–5285.CrossRefGoogle Scholar
  33. [33]
    D. W. Kang, H. J. Jang and T. S Kim, Using compressor discharge air bypass to enhance power generation of a steam–injected gas turbine for combined heat and power, Energy, 76 (2014) 390–399.Google Scholar
  34. [34]
    R. Eldrid, L. Kaufman and P. Marks, The 7FB: The next evolution of the F gas turbine, GE Power Systems (2001) Report No.: GER–4194.Google Scholar
  35. [35]
    R. Farmer, Gas turbine world 2008 Performance specs, Twenty fifth Ed., Pequot Publishing Inc, North Carolina, USA (2008).Google Scholar
  36. [36]
    S. W. Smith, The Scientist and engineer’s guide to digital signal processing, Second Ed., California Technical Publishing, California, USA (1997).Google Scholar
  37. [37]
    A. P. Tarabrin, V. A. Schurovsky, A. I. Bodrov and J. P. Stalder, Influence of axial compressor fouling on gas turbine unit performance based on different schemes and with different initial parameters, International Gas Turbine and Aeroengine Congress and Exposition, Stockholm, Sweden (1998) 98–GT–416.Google Scholar
  38. [38]
    P. F. Batcho, J. C. Moller, C. Padova and M. G. Dunn, Interpretation of gas turbine response due to dust ingestion, Journal of Engineering for Gas Turbines and Power, 109 (3) (1987) 344–352.CrossRefGoogle Scholar
  39. [39]
    M. S. Grewal, Gas turbine engine performance deterioration modelling and analysis, Ph.D. Thesis, Cranfield University, UK (1988).Google Scholar
  40. [40]
    P. C. Escher, An object–oriented gas path analysis computer program for general applications, Ph.D. Thesis, Cranfield University, UK (1995).Google Scholar
  41. [41]
    E. Mohammadi and M. Montazeri–Gh, Simulation of full and part–load performance deterioration of industrial twoshaft gas turbine, Journal of Engineering for Gas Turbines and Power, 136 (9) (2014) 092602–1–092602–9.CrossRefGoogle Scholar
  42. [42]
    M. J. Kim, J. H. Kim and T. S. Kim, The effects of internal leakage on the performance of a micro gas turbine, Applied Energy, 212 (2018) 175–184.CrossRefGoogle Scholar
  43. [43]
    A. P. Tarabrin, V. A. Schurovsky, A. I. Bodrov and J. P. Stalder, An analysis of axial compressors fouling and a cleaning method of their blading, International Gas Turbine and Aeroengine Congress and Exposition, Birmingham, UK (1996) 96–GT–363.Google Scholar
  44. [44]
    F. J. Brooks, GE gas turbine performance characteristics, GE Power Systems (2000) Report No.: GER–3567H.Google Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Graduate SchoolInha UniversityIncheonKorea
  2. 2.Department of Mechanical EngineeringInha UniversityIncheonKorea

Personalised recommendations