Artificial intelligence for the diagnostics of gas turbines - Part 1: Neural network approach

Journal of Engineering for Gas Turbines and Power

Volumn 129, Issue 3, 2007, Pages 711-719

  Bettocchi, R ^a   Pinelli, M ^a   Spina, P R ^a   Venturini, M ^a  

^a UNIVERSITY OF FERRARA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; COMPRESSORS; FEEDFORWARD NEURAL NETWORKS; MEASUREMENT ERRORS; ROBUSTNESS (CONTROL SYSTEMS); UNCERTAINTY ANALYSIS;

COMPUTATIONAL TIME; FLOW PASSAGE;

GAS TURBINES;

BACKPROPAGATION; COMPRESSORS; FEEDFORWARD NEURAL NETWORKS; GAS TURBINES; MEASUREMENT ERRORS; ROBUSTNESS (CONTROL SYSTEMS); UNCERTAINTY ANALYSIS;

EID: 34848896254     PISSN: 07424795     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.2431391     Document Type: Article

References (50)

1. Hoeft, R. F., 1996, "Heavy Duty Gas Turbine Operating & Maintenance Considerations," Proc. of 39th GE Turbine State-of-the-Art Technology Seminar, GE ed., Schenectady, NY, August 26-29, Paper No. GER-3620D.
2. Rajamani, R., Wang, J., and Jeong, K.-Y., 2004, "Condition-Based Maintenance for Aircraft Engines," ASME Paper No. GT2004-54127.
3. Meher-Homji, B. C., and Cullen, P. J., 1992, "Integration of Condition Monitoring Technologies for the Health Monitoring of Gas Turbines," ASME Paper No. 92-GT-52.
4. Meher-Homji, B. C., Boyce, P. M., Lakshminarashima, A. N., Whitten, A. J., and Meher-Homji, J. F., 1993, "Condition Monitoring and Diagnostic Approaches for Advanced Gas Turbines," Proc. of 7th ASME COGEN-TURBO, Bournemouth, UK, IGTI Vol. 9, pp. 347-354.
5. Madej, J., Longtin, K., and Smith, D. P., 1996, "Monitoring Service Delivery System and Diagnostics," Proc. of 39th GE Turbine State-of-the-Art Technology Seminar, GE ed., Schenectady, NY, August 26-29, Paper No. GER-3956.
6. Tsalavoutas, A., Aretakis, N., Mathioudakis, K., and Stamatis, A., 2000, "Combining Advanced Data Analysis Methods for the Constitution of an Integrated Gas Turbine Condition Monitoring and Diagnostic System," ASME Paper No. 2000-GT-0034.
7. Bettocchi, R., Pinelli, M., Spina, P. R., Venturini, M., and Sebastanelli, S., 2001, "A System for Health State Determination of Natural Gas Compression Gas Turbines," ASME Paper No. 2001-GT-0223.
8. Veer, T., Ulvestad, A., and Bolland, O., 2004, "Frame, a Toll for Predicting Gas Turbine Condition as Well as Reliability, Availability Performance," ASME Paper No. GT2004-53770.
9. Byington, C. S., Roemer, M. J., Watson, M. J., Galie, T. R., and Savage, C., 2004, "Prognostic Enhancement to Diagnostic Systems (PEDS) Applied to Shipboard Power Generation Systems," ASME Paper No. GT2004-54135.
10. Li, Y. G., 2002, "Performance Analysis Based Gas Turbine Diagnostics: A Review," Proc. Inst. Mech. Eng., Part A, 216, pp. 363-377.
11. Urban, L. A., 1972, "Gas Path Analysis Applied to Turbine Engine Condition Monitoring," Proc. of AIAA/SAE 8th Joint Propulsion Conference, New Orleans, AIAA, Washigton, DC, AIAA Paper No. 72-1082.
12. Stamatis, A., and Papailiou, K. D., 1988, "Discrete Operating Conditions Gas Path Analysis," Proceedings, AGARD Conference, Quebec, Canada, pp. 33-1-33-10.
13. Urban, L. A., and Volponi, A. J., 1992, "Mathematical Methods of Relative Engine Performance Diagnostics," SAE Trans., 101, p. 922048.
14. Doel, D. L., 1994, "TEMPER - A Gas-Path Analysis Tool for Commercial Jet Engines," ASME J. Eng. Gas Turbines Power, 116, pp. 82-89.
15. Doel, D. L., 1994, "An Assessment of Weighted-Least-Squares Based Gas Path Analysis," ASME J. Eng. Gas Turbines Power, 116, pp. 366-373.
16. Stamatis, A., Mathioudakis, K., and Papailiou, K. D., 1990, "Adaptive Simulation of Gas Turbine Performance," ASME J. Eng. Gas Turbines Power, 112, pp. 168-175.
17. Benvenuti, E., Bettocchi, R., Cantore, G., Negri di Montenegro, G., and Spina, P. R., 1993, "Gas Turbine Cycle Modeling Oriented to Component Performance Evaluation from Limited Design or Test Data," Proc. of 7th ASME COGEN-TURBO, Bournemouth, UK, ASME, New York, IGTI Vol. 8, pp. 327-337.
18. Bettocchi, R., and Spina, P. R., 1999, "Diagnosis of Gas Thrbine Operating Conditions by Means of the Inverse Cycle Calculation," ASME Paper No. 99-GT-185.
19. Pinelli, M., Spina, P. R., and Venturini, M., 2003, "Optimized Operating Point Selection for Gas Turbine Health State Analysis by Using a Multi-Point Technique," ASME Paper No. GT2003-38191.
20. Jang, J.-S. R., Sun, C.-T., and Mizutani, E., 1997, Neuro-Fuzzy and Soft Computing, Prentice-Hall, Englewood Cliffs, NJ.
21. Torella, G., and Lombardo, G., 1996, "Neural Networks for the Diagnostics of Gas Turbine Engines," ASME Paper No. 96-TA-39.
22. Kanelopoulos, K., Stamatis, A., and Mathioudakis, K., 1997, "Incorporating Neural Networks Into Gas Turbine Performance Diagnostics," ASME Paper No. 97-GT-35.
23. Volponi, A. J., DePold, H. R., Ganguli, R., and Daguang, C., 2000, "The Use of Kalman Filter and Neural Networks Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study," ASME Paper No. 2000-GT-0547.
24. Romessis, C., Stamatis, A., and Mathioudakis, K., 2001, "A Parametric Investigation of the Diagnostic Ability of Probabilistic Neural Networks on Turbo-fan Engines," ASME Paper No. 2001-GT-0011.
25. Bettocchi, R., Spina, P. R., and Torella, G., 2002, "Gas Turbine Health Indices Determination by Using Neural Networks," ASME Paper No. GT-2002-30276.
26. Arriagada, J., Genrup, M., Loberg, A., and Assadi, M., 2003, "Fault Diagnosis System for an Industrial Gas Turbine by Means of Neural Networks," Proc. International Gas Turbine Congress 2003 (IGTC'013), Tokyo, Nov. 2-7, GTSJ, Tokyo, Paper No. IGTC2003, Tokyo TS-001.
27. Sampath, S., and Singh, R., 2004, "An Integrated Fault Diagnostics Model Using Genetic Algorithm and Neural Networks," ASME Paper No. GT-2004-53914.
28. Ganguli, R., 2003, "Application of Fuzzy Logic for Fault Isolation of Jet Engines," ASME J. Eng. Gas Turbines Power, 125, pp. 617-623.
29. Ganguli, R., Verma, R., and Roy, N., 2004, "Soft Computing Application for Gas path Fault Isolation," ASME Paper No. GT-2004-53209.
30. Console, L., and Torasso, P., 1989, Diagnostic Problem Solving: Combining Heuristic, Approximate and Causal Reasoning, Van Nostrand Reinhold, New York.
31. Doel, D. L., 1990, "The Role of Expert Systems in Commercial Gas Turbine Engine Monitoring," ASME Paper No. 90-GT-374.
32. Turella, G., 1992, "Expert Systems for the Trouble-Shooting and the Diagnostics of Engines," ALAA Paper No. 92-3327.
33. Palmer, C. A., 1998, "Combining Bayesian Belief Networks With Gas Path Analysis for Test Cell Diagnostics and Overhaul," ASME Paper No. 98-GT-168.
34. DePold, H. R., and Gass, F. D., 1999, "The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics," ASME J. Eng. Gas Turbines Power, 121, pp. 607-612.
35. Spina, P. R., Torella, G., and Venturini, M., 2002, "The Use of Expert Systems for Gas Turbine Diagnostics and Maintenance," ASME Paper No. GT-2002-30033.
36. Jain, L. C., and Martin, N. M., 1998, Fusion of Neural Networks, Fuzzy Sets, and Genetic Algorithms, CRC Press, Boca Raton.
37. Bettocchi, R., Pinelli, M., Venturini, M., Spina, P. R., Bellagamba, S., and Tirone, G., 2002, "Procedura di Calibrazione del Programma per la Diagnosi Funzionale dei Turbogas della Centrale a Ciclo Combinato di La Spezia," Proc. 57th Congresso Nazionale ATI, Pisa, Italy, ETS ed., September 17-20, pp. III-B-3-III-B-12 (in Italian).
38. Stamatis, A., Mathioudakis, K., and Papailiou, K., 1992, "Optimal Measurement and Health Index Selection for Gas Turbine Performance Status and Fault Diagnosis," ASME J. Eng. Gas Turbines Power, 114, pp. 209-216.
39. Bettocchi, R., Spina, P. R., and Benvenuti, E., 2000, "Set-Up of an Adaptive Method for the Diagnosis of Gas Turbine Operating State by Using Test-Bench Measurements," ASME Paper No. 2000-GT-0309.
40. Mathioudakis, K., and Tsalavoutas, A., 2001, "Uncertainty Reduction in Gas Turbine Performance Diagnostics by Accounting for Humidity Effects," ASME Paper No. 2001-GT-0010.
41. Pinelli, M., and Spina, P. R., 2002, "Gas Turbine Field Performance Determination: Sources of Uncertainties," ASME J. Eng. Gas Turbines Power, 124, pp. 155-160.
42. Mathioudakis, K., 2003, "Non-linear Methods for Gas Turbine Fault Diagnostics," Von Karman Institute Lecture Series 2003-01, Gas Turbine Monitoring & Fault Diagnosis, Jan. 13-17.
43. Mathioudakis, K., Kamboukos, Ph., and Stamatis, A., 2002, "Turbofan Performance Deterioration Tracking Using Non-linear Models and Optimization Techniques," ASME Paper No. GT-2002-30026.
44. Mathioudakis, K., and Kamboukos, Ph., 2004, "Assessment of the Effectiveness of Gas Path Diagnostic Schemes," ASME Paper No. GT-2004-53862.
45. Haykin, S., 1999, Neural Networks - A Comprehensive Foundation, 2nd ed., Prentice-Hall, Englewood Cliffs, NJ.
46. Cybenko, G., 1989, "Approximation by Superimposition of a Sigraoidal Function," Math. Control, Signals, Syst., 2, pp. 303-314.
47. Rumenlhart, D. E., Hinton, G. E., and Williams, R. J., 1986, "Learning Internal Representation by Error Propagation, Parallel Distributed Processing," Explor. Microstruct. Cognition, 1, pp. 318-362.
48. Bettocchi, R., Pinelli, M., Spina, P. R., and Venturini, M., 2003, Statistical Analyses to Improve Gas Turbine Diagnostics Reliability, Proc. of 8th International Gas Turbine Congress, 2003 (IGTC'03), Tokyo, November 2-7 GTSJ, Tokyo, Paper No. IGTC2003Tokyo TS-004.
49. Pinelli, M., and Venturini, M., 2002, "Application of Methodologies to Evaluate the Health State of Gas Turbines in a Cogenerative Combined Power Plant," ASME Paper No. GT-2002-30248.
50. Bettocchi, R., Pinelli, M., Spina, P. R., Venturini, M., and Burgio, M., 2004, "Set Up of a Robust Neural Network for Gas Turbine Simulation," ASME Paper No. GT2004-53421.