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Modeling cavitation erosion using non-homogeneous gamma process

Author

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  • Chatenet, Q.
  • Remy, E.
  • Gagnon, M.
  • Fouladirad, M.
  • Tahan, A.S.

Abstract

Although hydroelectric generating units are highly reliable, being able to accurately model their degradation level represents a real asset in industrial and financial risk management. This paper presents and models a common degradation phenomenon observed on hydraulic Francis turbine runners: erosive cavitation. It gives an application of stochastic processes for degradation modeling framework in presence of real laboratory experimental data. For degradation modeling, a non homogeneous gamma process is proposed. The model calibration is explained and asymptotic confidence intervals for the model estimate are assessed. Because of the limited size of available dataset, bootstrap techniques are also used to evaluate statistical estimation uncertainties on the model parameters. These uncertainties on the degradation model are then propagated in order to analyze how they impact the distribution of the system lifetime, characterized by the hitting time for a given degradation threshold.

Suggested Citation

  • Chatenet, Q. & Remy, E. & Gagnon, M. & Fouladirad, M. & Tahan, A.S., 2021. "Modeling cavitation erosion using non-homogeneous gamma process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    • Handle: RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002106
    DOI: 10.1016/j.ress.2021.107671
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    1. Cholette, Michael E. & Yu, Hongyang & Borghesani, Pietro & Ma, Lin & Kent, Geoff, 2019. "Degradation modeling and condition-based maintenance of boiler heat exchangers using gamma processes," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 184-196.
    2. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    3. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    4. Fouladirad, Mitra & Paroissin, Christian & Grall, Antoine, 2018. "Sensitivity of optimal replacement policies to lifetime parameter estimates," European Journal of Operational Research, Elsevier, vol. 266(3), pages 963-975.
    5. Le Son, Khanh & Fouladirad, Mitra & Barros, Anne, 2016. "Remaining useful lifetime estimation and noisy gamma deterioration process," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 76-87.
    6. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    7. N. Bousquet & M. Fouladirad & A. Grall & C. Paroissin, 2015. "Bayesian gamma processes for optimizing condition‐based maintenance under uncertainty," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(3), pages 360-379, May.
    8. Zhai, Qingqing & Chen, Piao & Hong, Lanqing & Shen, Lijuan, 2018. "A random-effects Wiener degradation model based on accelerated failure time," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 94-103.
    9. Wolfgang Härdle & Joel Horowitz & Jens‐Peter Kreiss, 2003. "Bootstrap Methods for Time Series," International Statistical Review, International Statistical Institute, vol. 71(2), pages 435-459, August.
    10. Christian Paroissin & Ali Salami, 2014. "Failure Time of Non Homogeneous Gamma Process," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(15), pages 3148-3161, August.
    11. Nguyen, Khanh T.P. & Fouladirad, Mitra & Grall, Antoine, 2018. "Model selection for degradation modeling and prognosis with health monitoring data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 105-116.
    12. Winfried Stute & Wenceslao Manteiga & Manuel Quindimil, 1993. "Bootstrap based goodness-of-fit-tests," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 40(1), pages 243-256, December.
    13. Zhibing Xu & Yili Hong & Ran Jin, 2016. "Nonlinear general path models for degradation data with dynamic covariates," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 32(2), pages 153-167, March.
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