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

Master Thesis (2021)
Author(s)

P. Rouwenhorst (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

V. L. Markine – Mentor (TU Delft - Railway Engineering)

JM Hendriks – Graduation committee member (TU Delft - Railway Engineering)

Nikola Bešinović – Graduation committee member (TU Delft - Transport and Planning)

Faculty
Civil Engineering & Geosciences
Copyright
© 2021 Paul Rouwenhorst
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Paul Rouwenhorst
Graduation Date
07-09-2021
Awarding Institution
Delft University of Technology
Faculty
Civil Engineering & Geosciences
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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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