Remaining useful life estimation based on stochastic deterioration models: A comparative study

Khanh Le Son (1) , Mitra Fouladirad (1) , Anne Barros (1) , Eric Levrat (2) , Benoît Iung (2)

1 LM2S - Laboratoire Modélisation et Sûreté des Systèmes
2 CRAN - Centre de Recherche en Automatique de Nancy

Prognostic of system life time is a basic requirement for condition-based maintenance in many application domains where safety, reliability, and availability are considered of first importance.This paper presents a probabilistic method for prognostic applied to the 2008 PHM Conference Challenge data. A stochastic process (Wiener process) combined with a data analysis method (Principal Component Analysis) is proposed to model the deterioration of the components and to estimate the RUL on a case study. The advantages of our probabilistic approach are pointed out and a comparison with existing results on the same data is made

Mots clés: Deterioration modelling; Principal component analysis; Stochastic process; Wiener process with drift; Prognostics; Remaining useful life time estimation

Domaines: Automatique / Robotique

Khanh Le Son, Mitra Fouladirad, Anne Barros, Eric Levrat, Benoît Iung. Remaining useful life estimation based on stochastic deterioration models: A comparative study. Reliability Engineering and System Safety, 2013, 112, pp.165-175. ⟨10.1016/j.ress.2012.11.022⟩. ⟨hal-00795347⟩