RESEARCH PAPER
Application of 1D convolutional neural networks for anomaly detection in resistance measurements of railway wheelsets
1
Łukasiewicz Research Network – Poznań Institute of Technology, Polska
2
Poznan University of Technology, Politechnika Poznańska, Polska
Submission date: 2025-06-13
Final revision date: 2025-08-19
Acceptance date: 2025-08-28
Online publication date: 2025-09-27
Publication date: 2025-09-27
Corresponding author
Tomasz Paweł Olejniczak
Łukasiewicz Research Network – Poznań Institute of Technology, Łukasiewicz Research Network – Poznań Institute of Technology, Ewarysta Estkowskiego 6, 61-755, Poznań, Polska
Łukasiewicz Research Network – Poznań Institute of Technology, Łukasiewicz Research Network – Poznań Institute of Technology, Ewarysta Estkowskiego 6, 61-755, Poznań, Polska
Rail Vehicles/Pojazdy Szynowe 2025,1-2,27-31
KEYWORDS
TOPICS
ABSTRACT
The article presents the application of convolutional neural networks (CNN) for the classification of electrical resistance measurements of railway wheelsets. The aim of the study was to develop a model capable of automatically detecting incorrect measurement results based on data obtained from various measurement configurations. The training process used experimental data collected under real-world conditions. The developed model achieved high classification accuracy and was tested on variable-length data. The study demonstrates that CNN-based methods can be effectively applied in the diagnostics of measurement systems.
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| eISSN: | 2719-9630 |
| ISSN: | 0138-0370 |
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