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Journals / Journal of Innovative Transportation / 2025 / Volume: 6 Issue: 2

A study on wavelet analysis of railway track geometry

Murat Vergi Taciroğlu(MERSİN ÜNİVERSİTESİ)0000-0002-0672-1672
Hakan Işıker(MERSIN UNIVERSITY, FACULTY OF ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING)0000-0002-6465-8480
Pages
—
Publication Date
2025-12-16
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that geometric defects of different wavelengths that cannot be detected by tolerance-based assessment methods in track geometry graphs can be detected along with their locations using the wavelet analysis method.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Repeated train passages and environmental conditions cause deterioration of the geometric conditions of railway lines.
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Key Findings & Data:However, these defects cannot be accurately detected with assessments based on threshold values specified in standards such as EN 13848.
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Conclusion & Impact:The results show that geometric defects of different wavelengths that cannot be detected by tolerance-based assessment methods in track geometry graphs can be detected along with their locations using the wavelet analysis method.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Track geometry · Wavelet analysis · Mexican hat

Abstract

Repeated train passages and environmental conditions cause deterioration of the geometric conditions of railway lines. When track geometry graphs are examined, it is seen that railway tracks have a rough, wavy form due to geometric deterioration. The wavy form of the track geometry contains many geometric defects of different wavelengths. However, these defects cannot be accurately detected with assessments based on threshold values specified in standards such as EN 13848. In this study, an approach based on the wavelet analysis method is proposed to determine geometric defects of different wavelengths in track geometry. For this purpose, the frequency spectrum of the measured longitudinal level data was first plotted and the highest frequency values were determined. The obtained frequency values were used to generate “Mexican Hat” functions, making the geometric data suitable for wavelet analysis. In the final stage, the locations of defects of different wavelengths were determined based on their frequencies as a result of the analysis. The results show that geometric defects of different wavelengths that cannot be detected by tolerance-based assessment methods in track geometry graphs can be detected along with their locations using the wavelet analysis method.

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Cite This Article

Taciroğlu, M. V., Işıker, H. (2025). A study on wavelet analysis of railway track geometry. Journal of Innovative Transportation, Volume: 6 Issue: 2. https://doi.org/10.53635/jit.1746351

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