Petra Wilfling & Michael Fellinger
Research associates with focus on life cycle considerations of turnouts at the Institute of Railway Engineering and Transport Economy at Graz University of Technology
Prediction of turnout behavior – From manual inspections to automated data analysis
To monitor and forecast the condition of turnouts, currently manual inspections are carried out. Due to the fact, that the necessary tasks are done without load impact and the measurements are rarely reproducible, another approach has to be found. Analysis have shown that it is already possible to carry out a large part of the necessary inspection tasks in an automated and loaded manner. Various Life-Cycle-considerations and expert interviews were carried out to identify the most critical parts of turnouts. The first evaluation identified the ballast and the substructure as those components, which are primarily responsible for concrete sleeper turnout’s service life . For those with wooden sleepers, the limiting components are the sleepers itself especially the friction between sleeper material and screws. Therefore, the measurement data from the track-recording car of the Austrian Federal Railways are used for a predictable description. In order to be able to describe the components based on measurement data, a detailed and intelligent re-stationing routine is necessary. Subsequently, the longitudinal level signal is used to assess the ballast condition. Wavelength analyses attempt to identify the cause for high deterioration rates at an early stage in order to initiate suitable countermeasures. To describe the condition of sleepers within turnouts, primarily the rail gauge signal is pursued. Unfortunately, the signal of the gauge measurement is not present over the entire length and so new ideas have to be found. At the end, all of the shown aspects represent the input data for “CoMPAcT” which is a tool for the condition monitoring and the prognosis of turnouts.
Petra Wilfling and Michael Fellinger are working as research associates at the Institute of Railway Engineering and Transport Economy at Graz University of Technology in Austria. They studied Civil Engineering – Infrastructure and graduated in 2017 / 2016. In their research, they deal with data analyses for turnouts, with the idea of smart infrastructure components as well as with life cycle cost analyses. Furthermore both attend the doctoral program for civil Engineering Sciences with research focus on turnouts.