Wheel-Rail Interface Condition Estimation (W-RICE)

TL;DR

This paper proposes a novel method to estimate wheel-rail adhesion conditions by analyzing rolling noise patterns, which are influenced by surface roughness and third-body presence, impacting noise levels.

Contribution

The study introduces a new approach that uses rolling noise analysis to assess wheel-rail interface conditions, enhancing non-invasive monitoring techniques.

Findings

Effective estimation of adhesion conditions from noise patterns

Correlation between noise levels and interface surface roughness

Potential for improved noise-based condition monitoring

Abstract

The surface roughness between the wheel and rail has a huge influence on rolling noise level. The presence of the third body such as frost or grease at wheel-rail interface contributes towards change in adhesion coefficient resulting in the generation of noise at various levels. Therefore, it is possible to estimate adhesion conditions between the wheel and rail from the analysis of noise patterns originating from wheel-rail interaction. In this study, a new approach to estimate adhesion condition is proposed which takes rolling noise as input.