Modelling track geometry by a bivariate Gamma wear process, with application to maintenance - Archive ouverte HAL Access content directly
Book Sections Year : 2009

Modelling track geometry by a bivariate Gamma wear process, with application to maintenance

Abstract

This paper discusses the maintenance optimization of arailway track, based on the observation of two dependent randomlyincreasing deterioration indicators. These two indicators are mod-elled through a bivariate Gamma process constructed by trivariatereduction. Empirical and maximum likelihood estimators are givenfor the process parameters and tested on simulated data. The EMalgorithm is used to compute the maximum likelihood estimators. Abivariate Gamma process is then fitted to real data of railway trackdeterioration. Preventive maintenance scheduling is studied, ensuringthat the railway track keeps a good quality with a high probability.The results are compared to those based on both indicators takenseparately, and also on one single indicator (usually taken for currenttrack maintenance). The results based on the joined information areproved to be safer than the other ones, which shows the interest ofthe bivariate model.
Fichier principal
Vignette du fichier
Symposium 2009 MeierHirmer_Mercier_Roussignol.pdf (490.51 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-00868498 , version 1 (07-05-2021)

Identifiers

  • HAL Id : hal-00868498 , version 1

Cite

Sophie Mercier, C. Meier-Hirmer, M. Roussignol. Modelling track geometry by a bivariate Gamma wear process, with application to maintenance. xx. Risk and Decision Analysis in Maintenance Optimization and Flood Management, IOS Press, Delft, pp.123--136, 2009. ⟨hal-00868498⟩
71 View
13 Download

Share

Gmail Facebook X LinkedIn More