ATTENTION/WARNING - NE PAS DÉPOSER ICI/DO NOT SUBMIT HERE

Ceci est la version de TEST de DIAL.mem. Veuillez ne pas soumettre votre mémoire sur ce site mais bien à l'URL suivante: 'https://thesis.dial.uclouvain.be'.
This is the TEST version of DIAL.mem. Please use the following URL to submit your master thesis: 'https://thesis.dial.uclouvain.be'.
 

Auto-calibration of wheel diameters

Spronck, Guillaume
(2024)

Files

Spronck_48131900_2024.pdf
  • Open access
  • Adobe PDF
  • 9.58 MB

Details

Supervisors
Pelsser, Cristel
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil en informatique, à finalité spécialisée
Abstract
Accurate measurement of train speed and position is required to guarantee the safety and effectiveness of railway operations. Wheel sensors, GNSS (Global Navigation Satellite System), and Doppler radar techniques combine to achieve precise measurements. However, obstacles like wheel slipping, signal loss, or even wheel wear can compromise the accuracy of these techniques. Engineers are currently working on developing robust positioning methods to improve traffic efficiency and reduce costs. Machine learning and data science algorithms can analyze data to identify patterns associated with wear or sensor drift. Self-diagnostic sensors can improve the reliability of a system and reduce the need for frequent manual calibration. This study aims to develop automated wheel diameter measurement methods for auto-calibration. This will enhance the efficiency of railways by lowering life-cycle expenses and simplifying maintenance procedures. GNSS-based Reference Speed, the chosen solution, uses the GNSS-measured speed as a reference speed to re-calibrate wheel diameters.