Predicting railway wheel wear under uncertainty of wear coefficient, using universal kriging

Marzia A. Cremona, Binbin Liu, Yang Hu, Stefano Bruni and Roger Lewis

Reliability Engineering and System Safety, 2016, vol. 154, issue C, 49-59

Abstract: Railway wheel wear prediction is essential for reliability and optimal maintenance strategies of railway systems. Indeed, an accurate wear prediction can have both economic and safety implications. In this paper we propose a novel methodology, based on Archard's equation and a local contact model, to forecast the volume of material worn and the corresponding wheel remaining useful life (RUL). A universal kriging estimate of the wear coefficient is embedded in our method. Exploiting the dependence of wear coefficient measurements with similar contact pressure and sliding speed, we construct a continuous wear coefficient map that proves to be more informative than the ones currently available in the literature. Moreover, this approach leads to an uncertainty analysis on the wear coefficient. As a consequence, we are able to construct wear prediction intervals that provide reasonable guidelines in practice.

Keywords: Wear prediction; Wear coefficient; Universal kriging; Remaining useful life (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:154:y:2016:i:c:p:49-59

DOI: 10.1016/j.ress.2016.05.012

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