Abstract
This paper focuses on the experimental study of an alteration in the railway crossing dynamic response due to the rolling surface degradation during a crossing’s lifecycle. The maximal acceleration measured with the track-side measurement system as well as the impact position monitoring show no significant statistical relation to the rolling surface degradation. The additional spectral features are extracted from the acceleration measurements with a wavelet transform to improve the information usage. The reliable prediction of the railway crossing remaining useful life (RUL) demands the trustworthy indicators of structural health that systematically change during the lifecycle. The popular simple machine learning methods like principal component analysis and partial least square regression are used to retrieve two indicators from the experimental information. The feature ranking and selection are used to remove the redundant information and increase the relation of indicators to the lifetime.
Highlights
A turnout is an important part of railway superstructure that provides trains passing from one railway track to another without the run interruption
The aim of this paper is to develop simple structural health indicators that are based on track side inertial measurements and are able to describe the state change during the lifecycle of a common crossing
The idea behind the principal components analysis (PCA) consists in constructing the linear combinations, or directions, that represent the predictors the best [31, 36, 37]
Summary
A turnout is an important part of railway superstructure that provides trains passing from one railway track to another without the run interruption. Turnouts are very expensive compared to ordinary tracks due to their constructive features. Because of their relative small length in overall railway network they share about 10% of the superstructure investment [1]. In terms of maintenance costs, this ratio of costs is substantially reversed. The track maintenance costs share about 50% of the overall infrastructure maintenance costs i.e. signal systems, catenary systems and engineering structures [1]. The turnout maintenance takes over a half of the track maintenance costs
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