Research data supporting chapter 'A Hybrid Neural Model Approach for Health Assessment of Transition Zones with Multiple Data' of dissertation 'AI Solutions for Maintenance Decision Support in Railway Infrastructure'

DOI:10.4121/43b96757-fd3f-4e89-b9ac-e0caad30f0f0.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/43b96757-fd3f-4e89-b9ac-e0caad30f0f0
Datacite citation style:
Phusakulkajorn, Wassamon ; Unsiwilai, Siwarak; Chang, Ling; Núñez, Alfredo ; Li, Zili (2024): Research data supporting chapter 'A Hybrid Neural Model Approach for Health Assessment of Transition Zones with Multiple Data' of dissertation 'AI Solutions for Maintenance Decision Support in Railway Infrastructure'. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/43b96757-fd3f-4e89-b9ac-e0caad30f0f0.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

The data and codes were prepared and uploaded to 4TU.ResearchData by Wassamon Phusakulkajorn to support the results in Chapter 5 (A Hybrid Neural Model Approach for Health Assessment of Transition Zones with Multiple Data) of her dissertation. This chapter has been submitted for publication as Phusakulkajorn, W., Unsiwilai, S., Chang, L., Núñez, A., Li, Z., A Hybrid Neural Model Approach for Health Assessment of Railway Transition Zones with Multiple Data Sources. In this research, we develop a framework that enables a more frequent evaluation of transition zone health by integrating multiple monitoring technologies, including track geometry measurements, interferometric synthetic aperture radar (InSAR), and axle box acceleration (ABA). This aims to improve an early detection capability for track irregularities. The data used in this research contain ABA, track geometry, InSAR measurements at transitions zone collected from a railway bridge between Dordrecht and Lage Zwaluwe station in the Netherlands. All implementations are done in MATLAB, where (.mat) files are analytical solutions and (.eps) and (.jpg) are figures used in the main manuscript.

History

  • 2024-07-22 first online, published, posted

Publisher

4TU.ResearchData

Format

.zip package, containing Matlab data (.mat), Matlab codes (.m), Matlab figure (.fig), figure (.eps), ReadMe file (.txt).

Funding

  • ProRail ProRail
  • IAM4RAIL - Holistic and Integrated Asset Management for Europe’s RAIL System (grant code 101101966) Europe’s Rail Flagship Project

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Engineering Structures, Section of Railway Engineering

DATA - restricted access

Reason

The data used belong to the railway infrastructure manager and are confidential, and the simulation models and codes are intended for this research project.

End User Licence Agreement

Access rights must be given by the supervisor (Zili Li Z.Li@tudelft.nl) before access.

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