ENBIS-18 in Nancy
2 – 25 September 2018; Ecoles des Mines, Nancy (France)
Abstract submission: 20 December 2017 – 4 June 2018
Modelling and Inference of Partially Observed Competing and Propagating Flaw Indications
5 September 2018, 11:10 – 11:30
- Submitted by
- Emmanuel REMY
- Emmanuel Remy (EDF R&D), Sophie Mercier (University of Pau), Laurent Bordes (University of Pau), Emilie Dautreme (EDF R&D)
- Passive components within EDF (Électricité de France - Electricity of France) electric power plants are periodically controlled in order to ensure that their degradation is lower than a critical level and to guarantee the safety and the availability of the installations. The physical deterioration of these systems consists in flaw indications, which first initiate one by one and then independently propagate over time. The inspections are carried out at discrete times and the non-destructive testing process allows to measure the size of the largest flaw indication, together with the total number of existing indications on each component. Although detected, too small indications cannot be measured, leading to censored observations.
Taking into account this partial information coming from the field, a specific stochastic model is developed. We consider that the flaw indications initiate according to a Poisson process and next propagate according to competing independent gamma processes. A parametric estimation procedure is proposed and applied to the real dataset. The fitted model is then used to assess useful indicators for reliability and maintenance engineers, such as the distribution of the residual operating time of the component until its degradation reaches the specified degradation threshold.
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