期刊
STRUCTURE AND INFRASTRUCTURE ENGINEERING
卷 8, 期 4, 页码 357-366出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/15732479.2011.563090
关键词
Gamma wear process; Levy process; dependent stochastic processes; reliability; track maintenance; rail track design; inspection; deterioration; mathematical modeling
This article discusses the intervention scheduling of a railway track, based on the observation of two dependent randomly increasing deterioration indicators. These two indicators are modelled through a bivariate Gamma process constructed by trivariate reduction. Empirical and maximum likelihood estimators are given for the process parameters and tested on simulated data. An expectation-maximisation (EM) algorithm is used to compute the maximum likelihood estimators. A bivariate Gamma process is then fitted to real data of railway track deterioration. Intervention scheduling is defined, ensuring that the railway track remains of good quality with a high probability. The results are compared to those based on both indicators taken separately, and also on one single indicator. The policy based on the joint information is proved to be safer than the other ones, which shows the potential of the bivariate model.
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