Wheel-Rail Interface Condition Estimation (W-RICE)
Audio and Speech Processing
2020-12-25 v1 Machine Learning
Sound
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.
Cite
@article{arxiv.2012.13096,
title = {Wheel-Rail Interface Condition Estimation (W-RICE)},
author = {Sundar Shrestha and Anand Koirala and Maksym Spiryagin and Qing Wu},
journal= {arXiv preprint arXiv:2012.13096},
year = {2020}
}
Comments
8 pages, 3 figures, JRC2020 conference