A reliability evaluation study based on competing failures for aircraft engines

• Autorzy: Wang H. , Gao J.

Warianty tytułu

PL

Badania dotyczące oceny niezawodności silników lotniczych w oparciu o uszkodzenia konkurujące

• Języki publikacji: EN

Abstrakty

EN

Aircraft engine is a complex and repairable system, and the diversity of its failure modes increases the difficulty of reliability evaluation. It is necessary to establish a dynamic relationship among data, failure mode and system reliability, to achieve the scientific reliability evaluation for aircraft engines. This paper has used data fusion method to establish reliability evaluation models respectively for performance degradation failures and sudden failures. Furthermore, these two models have been integrated on the basis of competing failures’ mechanism. Bayesian model averaging has been used to analyze the impacts of performance degradation failures and sudden failures on aircraft engines’ reliability. As a result of above, the goal of an accurate evaluation of the reliability for aircraft engines has been achieved. Example shows the effectiveness of the proposed model.

PL

Silnik samolotu to złożony system naprawialny, w którym różnorodność przyczyn uszkodzeń zwiększa trudność oceny niezawodności. Dlatego też istnieje konieczność ustalenia dynamicznych związków pomiędzy danymi, przyczynami uszkodzenia i niezawodnością systemu, których znajomość pozwoliłaby przeprowadzać naukową ocenę niezawodności silników lotniczych. W prezentowanej pracy wykorzystano metodę fuzji danych do opracowania modeli oceny niezawodności w zakresie uszkodzeń wynikających z obniżenia charakterystyk oraz uszkodzeń nagłych. Ponadto, opracowane modele zintegrowano na podstawie mechanizmu uszkodzeń konkurujących. Do analizy wpływu dwóch omawianych typów uszkodzeń na niezawodność silników lotniczych wykorzystano procedurę bayesowskiego uśredniania modeli. Dzięki powyższym krokom, osiągnięto założony cel dokładnej oceny niezawodności silników samolotowych. Przykład pokazuje skuteczność proponowanego modelu.

Słowa kluczowe

EN

aircraft engine; reliability evaluation; competing failures; Bayesian model averaging; data fusion

PL

silnik lotniczy; ocena niezawodności; uszkodzenia konkurujące; bayesowskie uśrednianie modeli; fuzja danych

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2014
• Tom: Vol. 16, no. 2
• Strony: 171--178
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Wang H.

• Nanjing University of Aeronautics and Astronautics Nanjing, Jiangsu210016, China

autor

Gao J.

• Department of Management Shijiazhuang Mechanical Engineering College Shijiazhuang, Heibei050003, China

Bibliografia

• 1. Bagdonavičius V, Bikelis A, Kazakevičius V et al. Analysis of joint multiple failure mode and linear degradation data with renewals. Journal of Statistical Plaaning and Inference, 2007;137(7): 2191–2207.
• 2. Bedford T. Competing risk modeling in reliability. In Modern statistical and mathematical methods in reliability. Edited by Wilson A, Limnios N, KellyMcNuly S et al.Word Scientific Publisher, New Jersey.
• 3. Bedford T, Dewan I, Meileijson I. The signal model: A model for competing risks of opportunistic maintenance. European Journal of Operational Research, 2011; 214(3): 665–673.
• 4. Bocchetti D, Giorgio M, Guida M et al. A competing risk model for the reliability of cylinder lines in marine Diesel engines. Reliability Engineering and System Safety, 2009; 94(8):1299–1307.
• 5. Chen BE, Lramer JL, Greene MH. Competing risk analysis of correlated failure time data. Biometrics, 2008;64(1):172–179.
• 6. Cobel JB. Merging data sources to predict remaining useful life-An automated method to identify prognostic parameters. University of Teenessee, Knoxville, 2010.
• 7. Kenneth P. Measuring the Performance of a HUM System – the Features that Count. Proceeding of Third International Conference on Health and Usage Monitoring – HUMS2003 . DSTO Platforms Sciences Laboratory, Australia 2003, 5–15.
• 8. Kundu D, Sarhan AM. Analysis of incomplete data in presence of competing risks among several groups. IEEE Transactions on Reliability 2006; 55(2): 262 – 269.
• 9. Lehmann A. Joint modeling of degradation and failure time data. Journal of Statistical Planning and Inference 2009;139(5): 1693–706.
• 10. Niu G, Yang BS, Pecht M. Development of an optimized-based maintenance system by data fusion and reliability-centered maintenance. Reliability Engineering and System Safety 2010; 95(7): 786–796.
• 11. Pareek B, Kundu D, Kumar S. On progressively competing risks data for Weibull distributions. Computational ststistics and data analysis 2009; 53(12–1): 4083–4094.
• 12. Park C, Kulasekera KB. Parametric inference of incomplete data with competing risks among several groups. IEEE Transactions on Reliability2004; 53(1): 11–21.
• 13. Peng H, Feng QM, Coit DW. Reliability and maintenance modeling for systems subject to multiple dependent competing failure process. IIE Transactions 2011,43(5): 12–22.
• 14. Polpo A, Sinha D.Correction in Bayesian nonparametric estimation in a series system or a competing-risk model. Statistics and Probability Letters 2011; 81(12): 1756–1759.
• 15. Salinas-Torres V, Pereira C, Tiwari R. Bayesian nonparametric estimation in a series system or a competing risks model. Journal of Nonparametric Statistics 2002; 14(4): 449–458.
• 16. Suarez EL, Duffy MI, Gamache RN et al. Jet engine life prediction systems integrated with prognostics health management. Proceeding of IEEE Aerospace Conference 2004; 3596–3602.
• 17. Su C, Zhang Y. System reliability assessment based on Wiener process and competing failure analysis .Journal of Southeast University 2010; 26(4): 554–557.
• 18. Volponi A. Data fusion for enhanced aircraft engine prognostics and health management—Task 14: Program plan development. Pratt & Whitney Internal Memo 2001, 10.
• 19. Wang CP, Ghosh M. Bayesian analysis of bivariate competing risks model with covariates. Journal of Statistical Planning and Inference 2003; 115(2–1): 441–459.
• 20. Xing LD, Levitin G. Combinatorial analysis of systems with competing failures subject to failure isolation and propagation effects. Reliability Engineering and System Safety 2010; 95(11): 1210–1215.