Monitoring of rail short pitch corrugation using the time-frequency features of both vertical and longitudinal axle box accelerations

Journal Article (2025)
Author(s)

S Li (TU Delft - Railway Engineering)

Pan Zhang (TU Delft - Railway Engineering)

A.A. Nunez Vicencio (TU Delft - Railway Engineering)

Rolf P.B.J. Dollevoet (TU Delft - Railway Engineering)

Zili Li (TU Delft - Railway Engineering)

Research Group
Railway Engineering
DOI related publication
https://doi.org/10.1016/j.measurement.2025.118064
More Info
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Publication Year
2025
Language
English
Research Group
Railway Engineering
Volume number
255
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Abstract

This paper presents a methodology for detecting and monitoring short pitch corrugation (SPC) under varying measurement conditions using vertical and longitudinal axle box acceleration (ABA) measurements. The main objective of the detection algorithm is to determine the likelihood and approximate severity of SPC presence, providing insights for maintenance planning. The methodology combines a validated three-dimensional finite element (3D-FE) model of the ABA responses at SPC and signal processing techniques to extract meaningful data from the real-world on-board measurements. First, a 3D-FE vehicle-track model is validated and used to quantify the physical relationships in the time–frequency responses of ABA at SPC under different levels of corrugation severity and measurement speeds. Then, a measurement train is instrumented with multiple accelerometers to capture field data on ABA at SPC, which is validated with field inspections and Railprof measurements. Finally, the ABA responses are analyzed based on the number of signals detecting SPC and an assessment of severity based on impact energy due to SPC. The methodology is demonstrated by analyzing the track between Assen and Groningen on the Dutch rail network. Results show that the methodology accurately detects registered SPC locations. Further, a whole track analysis is conducted, from which the methodology proposes new locations and severities of SPC, providing crucial information for rail maintenance planning.

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