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.
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