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Degradation prognosis based on a model of Gamma process mixture

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Abstract

A novel method is proposed to exploit jointly degradation measurements originating from a set of identical systems for making a degradation prognosis. The systems experience different degradation processes depending on operational conditions. The degradation processes are assumed to be Gamma processes. The aim is to cluster the degradation paths in classes corresponding to the different operational conditions in order to group properly the data for the estimation of degradation process parameters. A model of Gamma process mixture is considered and an expectation-minimization approach is proposed to estimate the unknown parameters. The feasibility of the method is shown on simulated cases. Prognosis results obtained with the proposed method are compared with results obtained with basic strategies (considering each system alone or all system together).
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Dates and versions

hal-02518573 , version 1 (25-03-2020)

Identifiers

  • HAL Id : hal-02518573 , version 1

Cite

Edith Grall-Maës, Pierre Beauseroy, Antoine Grall. Degradation prognosis based on a model of Gamma process mixture. Second European Conference of the Prognostics and Health Management Society 2014, Jun 2014, Nantes, France. ⟨hal-02518573⟩
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