Detection of Short-Section Ballast Breakdown in Track: A Fractal Analysis Approach with Reduced Window Size

Due to increasing demands on the available railway infrastructure, accurate estimates of safety-critical track condition as well as breakdowns of individual track components are crucial. This task can be supported by analyzing track measurement data. Ballast breakdown can be determined by analyzing the longitudinal level using fractal analysis: Commonly, a window with a width of 150 m is dragged over the signal computing an approximation of a fractal dimension of the signal for each position of the window. However, while a large window size can be used to describe the condition of ballast and substructure simultaneously, it fails to precisely localize short-section ballast breakdowns in the track. With the objective of describing and detecting these local effects in the ballast bed, this work analyzes a set of 114 known weak ballast spots. By reducing the width of the sliding window, the position of short-section ballast breakdowns can be reliably depicted. The application of a modified version of fractal analysis allows for a more accurate targeted maintenance on a component-specific basis.

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Publication Details

Journal
Fractal and Fractional
Published
2024-11-15
DOI
https://doi.org/10.3390/fractalfract8110664
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
0.00
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article

Detection of Short-Section Ballast Breakdown in Track: A Fractal Analysis Approach with Reduced Window Size

Stefan Marschnig, Stefan Offenbacher, Andrea Katharina Korenjak
Fractal and Fractional
Infrastructure Maintenance and Monitoring
article

Detection of Short-Section Ballast Breakdown in Track: A Fractal Analysis Approach with Reduced Window Size

Stefan Marschnig, Stefan Offenbacher, Andrea Katharina Korenjak
article en

Abstract

Due to increasing demands on the available railway infrastructure, accurate estimates of safety-critical track condition as well as breakdowns of individual track components are crucial. This task can be supported by analyzing track measurement data. Ballast breakdown can be determined by analyzing the longitudinal level using fractal analysis: Commonly, a window with a width of 150 m is dragged over the signal computing an approximation of a fractal dimension of the signal for each position of the window. However, while a large window size can be used to describe the condition of ballast and substructure simultaneously, it fails to precisely localize short-section ballast breakdowns in the track. With the objective of describing and detecting these local effects in the ballast bed, this work analyzes a set of 114 known weak ballast spots. By reducing the width of the sliding window, the position of short-section ballast breakdowns can be reliably depicted. The application of a modified version of fractal analysis allows for a more accurate targeted maintenance on a component-specific basis.

Fractal and FractionalVol. 8(11)
Graz University of Technology (AT)
Industry, innovation and infrastructure
Openalex Percentile: Top 77%
Infrastructure Maintenance and Monitoring
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