Gas turbine reliability model based on tangent hyperbolic reliability function

• Autorzy: Djeddi A. Z. , Hafaifa A. , Salam A.

Identyfikatory

DOI

10.15632/jtam-pl.53.3.723

• Języki publikacji: EN

Abstrakty

EN

The present work deals with the exploration of a new model proposed for the reliability analysis of industrial production systems. This proposed model is mainly based on the tangent hyperbolic function, where the survival function is determined and used in the lifetime distribution modeling taking into account of estimation the parameters of the proposed function. On the other side, tests validation is performed using the real data of a gas turbine installation. The obtained results allow the modeling of damage effects, hence the prediction of the performance of the examined gas turbine using the proposed model gives good results in terms of validity.

Słowa kluczowe

EN

reliability estimation; reliability algorithms; lifetime distribution; Weibull distribution; availability

• Wydawca: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
• Czasopismo: Journal of Theoretical and Applied Mechanics
• Rocznik: 2015
• Tom: Vol. 53 nr 3
• Strony: 723—730
• Opis fizyczny: Bibliogr. 20 poz, rys., tab.

Twórcy

autor

Djeddi A. Z.

• University of Djelfa, Faculty of Science and Technology, Djelfa, Algeria

autor

Hafaifa A.

• University of Djelfa, Faculty of Science and Technology, Djelfa, Algeria

autor

Salam A.

• University of Médéa, Faculty of Science and Technology, Médéa, Algeria

Bibliografia

• 1. Costa F.M.P., Rocha A.M.A.C., Fernandes E.M.G.P., 2014, An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method, Journal of Computational and Applied Mathematics, 259, Part B, 868-876
• 2. Guaily A.G., Epstein M., 2013, Boundary conditions for hyperbolic systems of partial differentials equations, Journal of Advanced Research, 4, 4, 321-329
• 3. Guemana M., Aissani S., Hafaifa A., 2011, Use a new calibration method for gas pipelines: an advanced method improves calibrating orifice flowmeters while reducing maintenance costs, Hydrocarbon Processing Journal, 90, 8, 63-68
• 4. Hafaifa A., Belhadef R., Guemana M., 2013a, Reliability model exploitation in industrial system maintainability using expert system evaluation, Proceedings of the 4th International Conference on Integrity, Reliability and Failure, IRF2013, Funchal, Madeira, Portugal, 387-388
• 5. Hafaifa A., Guemana M., Daoudi A., 2013b, Vibrations supervision in gas turbine based on parity space approach to increasing efficiency, Journal of Vibration and Control, doi: 10.1177/1077546313499927
• 6. Halimi D., Hafaifa A., Bouali E., 2014, Maintenance actions planning in industrial centrifugal compressor based on failure analysis, Journal of Maintenance and Reliability, 16, 1, 17-21
• 7. Hasumi T., Akimoto T., Aizawa Y., 2009, The Weibull-log Weibull distribution for interoccurrence times of earthquakes, Physica A: Statistical Mechanics and its Applications, 388, 4, 491-498
• 8. Lai C.D., 1994, Tests of univariate and bivariate stochastic ageing, IEEE Transactions on Reliability, 43, 2, 233-241
• 9. Lai C.D., Moore T., Xie M., 1998, The beta integrated model, Prococeding of the International Workshop on Reliability Modeling and Analysis: from Theory to Practice, 153-159
• 10. Lai C.D., Xie M., Murthy D.N.P., 2001, Bathtub shaped failure rate distributions, Handbook in Reliability, 20, 69-104
• 11. Lai C.D., Xie M., Murthy D.N.P., 2003, A modified Weibull distribution, IEEE Transactions on Reliability, 52, 1, 33-37
• 12. Moeini A., Jenab K., Mohammadi M., Foumani M., 2013, Fitting the three-parameter Weibull distribution with Cross Entropy, Applied Mathematical Modelling, 37, 9, 6354-6363
• 13. Murthy P.D.N., Xie M., Jiang R., 2004, Weibull Models, John Wiley & Sons
• 14. Rao C.R., Wegman E.J., Solka J.L., 2005, Handbook of Statistics: Data Mining and Data Visualization, Volume 24 de Handbook of Statistics, Elsevier Science
• 15. Ruji H., 1990, State space tree method and exact decomposition algorithm for finding network overall reliability, Journal of Electronics (China), 7, 4, 296-305
• 16. Scott D.W., 1979, On optimal and data-based histograms, Biometrika, 66, 3, 605-610
• 17. Sturges H.A., 1926, The choice of a class interval, Journal of the American Statistical Association, 21, 153, 65-66
• 18. Trofimov N.G., Kravchenko B.A., Kramarovskii B.I., Baturov V.B., Kostina G.N., 1978, Increasing the strength and reliability of turbine blades by thermoplastic hardening methods, Strength of Materials, 10, 8, 990-996
• 19. Weibull W., 1951, A statistical distribution function of wide applicability, Journal of Applied Mechanics, 1, 18, 293-297
• 20. Yang J., Scott D.W., 2013, Robust fitting of a Weibull model with optional censoring, Computational Statistics and Data Analysis, 67, 1, 149-161