Innovative Zustandserfassung des erweiterten Fahrwegs mittels LiDAR-Scanner

Translated title of the contribution: Innovative condition monitoring of the extended track by means of LiDAR-Scanner

Research output: ThesisMaster's Thesis

Abstract

Track condition monitoring and component’s assessment is of immense importance for the railway system. It forms the basis for planning of maintenance measures and thus enables for maintaining a high track quality. A wide variety of technologies are used to describe the condition of the track being continuously improved and evaluated. The LiDAR technology (Light Detection And Ranging) is not yet part of the applied measurement methods, but seems to have a great potential to be established as a measurement technology in the railway industry.
In this master’s thesis, the boundary conditions and system properties of the LiDAR technology are analyzed. Based on the findings, a potential analysis of the LiDAR technology for evaluating the condition of the extended track and in particular the ditches is carried out. For this purpose, a methodology is developed describing different factors of the extended track. It is further verified with georadar data and in-situ observations.
The correlation analysis between the georadar data and the LiDAR assessments shows slight correlations only. Strong correlations cannot be expected as the two measurement systems consider different factors. The observation of condition development over time for specific track sections shows that the LiDAR assessment method provides reliable and plausible results. Condition developments can be seen and stable evaluation results can be determined in different measurement runs. The methods used are undoubtedly not mature, but nevertheless deliver valid results. For this reason, LiDAR technology can be seen as having great potential for describing the condition of the extended track, provided that further in-depth research is carried out.
Translated title of the contributionInnovative condition monitoring of the extended track by means of LiDAR-Scanner
Original languageGerman
QualificationMaster of Science
Awarding Institution
  • Graz University of Technology (90000)
Supervisors/Advisors
  • Marschnig, Stefan, Supervisor
  • Landgraf, Matthias, Supervisor
Award date21 Nov 2022
Publication statusPublished - 26 Oct 2022

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