Influence of different railway lines on wheel damage of high-speed trains: Data-driven modelling and prediction

Yuanchen Zeng, Dongli Song, Weihua Zhang and Boqing Chen

Journal of Risk and Reliability, 2023, vol. 237, issue 6, 1088-1099

Abstract: Wheel damage of high-speed trains has received great attention since it is detrimental to safety and reliability and consumes huge maintenance costs. However, the mixed operation mode of electric multiple units (EMUs) in China induces great challenges in distinguishing the influence of different railway lines on wheel damage. This paper develops a data-driven approach to quantify the influence of different railway lines on wheel damage and further applies it to damage risk prediction. First, under several fundamental assumptions, linear discriminant analysis and the proposed data padding strategy are used to quantify the influence on wheel damage due to per unit mileage of running on each railway section. The result shows that the influence on wheel damage varies significantly for different railway sections. Then, a route-based predictor is defined to represent the cumulative influence of an EMU’s routes on its wheel damage. Further, a wheel damage prediction model is developed based on a support vector machine using the route-based predictor and three other predictors from the operational data. Validation and test results demonstrate that the actual damage rate is higher for wheelsets predicted with higher damage probabilities. The proposed methodology has the potential to be applied to the risk-based operation and maintenance of high-speed trains.

Keywords: Wheel damage; railway line; linear discriminant analysis; support vector machine; high-speed trains; electric multiple units (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X221122032 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:237:y:2023:i:6:p:1088-1099

DOI: 10.1177/1748006X221122032

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().