Reliability Analysis of Francis Turbine Cracking Using Gamma Frailty Model and Censored Historical Maintenance Data

Théophile Tshibangu, Guyh Ngoma, Martin Gagnon, Sébastien Carle

2024

Abstract

All over the world, the need for electrical energy has increased dramatically, forcing hydroelectric power plants to operate under non-standard conditions. This leads to premature fatigue cracking and consequently to multiples crack inspections. In this research, a probabilistic model is developed based on frailty and censoring. The model takes advantage of the use of a Non-Homogeneous Poisson Process (NHPP) because turbine runners are considered as repairable parts. We develop the marginal likelihood expression incorporating frailty effect using gamma frailty distribution and we use the stochastic gradient descent (SGD) algorithm to obtain the optimal parameters. Furthermore, instead of considering the frailty effect z as a random variable, we decide to derive its expression from the individual unconditional likelihood function that has been also optimized. Finally, we compare reliability and cumulative hazard functions between family members. We then confirm the results obtained by comparing reliability between two families that behaved differently. Results shows that frailty effect, that is fonction of failure statuses and individual final time of observation for a specific component has played an impor tant role in differentiating heterogeneity among groups of the same family. Reliability curves clearly demonstrate heterogeneity within and between families.

Paper Citation

in Harvard Style

Tshibangu T., Ngoma G., Gagnon M. and Carle S. (2024). Reliability Analysis of Francis Turbine Cracking Using Gamma Frailty Model and Censored Historical Maintenance Data. In Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-708-5, SciTePress, pages 128-137. DOI: 10.5220/0012813000003758

in Bibtex Style

@conference{simultech24,
author={Théophile Tshibangu and Guyh Ngoma and Martin Gagnon and Sébastien Carle},
title={Reliability Analysis of Francis Turbine Cracking Using Gamma Frailty Model and Censored Historical Maintenance Data},
booktitle={Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2024},
pages={128-137},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012813000003758},
isbn={978-989-758-708-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - Reliability Analysis of Francis Turbine Cracking Using Gamma Frailty Model and Censored Historical Maintenance Data
SN - 978-989-758-708-5
AU - Tshibangu T.
AU - Ngoma G.
AU - Gagnon M.
AU - Carle S.
PY - 2024
SP - 128
EP - 137
DO - 10.5220/0012813000003758
PB - SciTePress