PREDICTION MODELS FOR RUL ESTIMATION IN OIL AND GAS INDUSTRY

Authors

  • Dmytro Mahas Ivano-Frankivsk National Technical University of Oil and Gas http://orcid.org/
  • Vitalia Kropyvnytska Ivano-Frankivsk National Technical University of Oil and Gas http://orcid.org/0000-0001-5231-7104

DOI:

https://doi.org/10.30890/2567-5273.2022-22-01-046

Keywords:

 remaining useful life, RUL, predictive maintenance, oil and gas industry.

Abstract

 This article is focused on the usage of prediction models for remaining useful life (RUL) estimation. General scenarios for the usage of specific models for RUL estimation were presented.

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References

Okoh, C., Roy, R., Mehnen, J. and Redding, L. // Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services. Procedia CIRP, 16, 158–163.

Vaidya, P. (2010). Prognosis - subsea oil and gas industry // Annual Conference of the Prognostics and Health Management Society, 10 - 14 October, Portland, USA, pp. 1–10.

Gelman, A., Carlin, J.B., Stern, H.S. and Rubin, D.B. // Bayesian data analysis. Boca Raton, FL, USA: Chapman & Hall/CRC.

Si, X.S., Wang, W., Hu, C.H. and Zhou, D.H. // Remaining useful life estimation - A review on the statistical data driven approaches. European Journal of Operational Research, 213(1), 1–14.

Vaidya, P. and Rausand, M. // Remaining useful life, technical health, and life extension. Journal of Risk and Reliability, 225(2), 219–231.

Singpurwalla, N.D. // (1995) Survival in dynamic environments. Statistical Science, 1(10), 86-103

Siddique, A., Yadava, G.S. and Singh, B. // (2003) Applications of artificial intelligence techniques for induction machine stator fault diagnostics: review. In; 4th IEEE International Symposium Diagnostics for Electric Machines, Power Electronics and Drives, 24-26 August, Georgia USA, pp. 29–34.

Winning, I.G. and Belhimer, E. // (2006) Practical Aspects of Field Monitoring of Corrosion. In: NACE International Conferene, 12-16 March, San Diego, California, USA, pp. 1-18.

Published

2022-08-30

How to Cite

Магас, Д., & Кропивницька, В. (2022). PREDICTION MODELS FOR RUL ESTIMATION IN OIL AND GAS INDUSTRY. Modern Engineering and Innovative Technologies, 1(22-01), 38–41. https://doi.org/10.30890/2567-5273.2022-22-01-046

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Articles