Insulated Rail Joint defect recognition using frequency characteristics of the Axle Box Acceleration measurements

Master thesis (2021)

Authors

P. Rouwenhorst Civil Engineering & Geosciences

Contributors

V.L. Markine Railway Engineering - CEG (mentor)
J.M. Hendriks Railway Engineering - CEG (graduation committee member)
Nikola Bešinović (graduation committee member)
Faculty
Civil Engineering & Geosciences, Civil Engineering & Geosciences
Copyright: © 2021 Paul Rouwenhorst
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Published Date

07-09-2021

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

In this thesis Axle Box Acceleration (ABA) data is used to determine the health condition of Insulated Rail Joints (IRJs) to investigate the potential of ABA data in predictive maintenance. Using frequency characteristics from the Continuous Wavelet Transformation (CWT), the main research question “How can Axle Box Acceleration data be used in automatic classification of specific defect types at Insulated Rail Joints?” is investigated and answered.

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