Searched for: +
(1 - 3 of 3)
document
Phusakulkajorn, W. (author), Hendriks, J.M. (author), Moraal, J. (author), Shen, C. (author), Zeng, Y. (author), Unsiwilai, S. (author), Bogojevic, B. (author), Asplund, Matthias (author), Zoeteman, A. (author), Nunez, Alfredo (author), Dollevoet, R.P.B.J. (author), Li, Z. (author)
This work presents the results of a measurement campaign to demonstrate the effectiveness of the axle box acceleration (ABA) technology for detecting rail defects. The measurements were conducted along the Iron Ore line between Sweden and Norway for the IN2TRACK3 project. This line is mostly single-track with passenger-freight mixed traffic and...
conference paper 2024
document
Wang, L. (author), Unsiwilai, S. (author), Zeng, Y. (author), Shen, C. (author), Hendriks, J.M. (author), Moraal, J. (author), Zoeteman, A. (author), Nunez, Alfredo (author), Dollevoet, R.P.B.J. (author), Li, Z. (author)
Railway transition zones connecting conventional embankments and rigid struc-tures, such as bridges and tunnels, usually degrade much faster than other railway sections. Efficient health condition monitoring of transition zones is important for preventative track maintenance. In this paper, a methodology for monitoring rail-way transition zones...
conference paper 2024
document
Wang, H. (author), Hendriks, J.M. (author), Dollevoet, R.P.B.J. (author), Zoeteman, Arjen (author), Nunez, Alfredo (author)
Aiming to handle the increasing variety and volume of railway infrastructure monitoring data, this paper explores the use of intelligent data fusion methods for automatic anomaly detection of railway catenaries. Three classical data dimensionality reduction methods, namely the principal component analysis (PCA), the autoencoder neural network,...
conference paper 2022