Determination of the characteristics of punctual instabilities considering the occurring cause and load (EPIB 1.1)

Damaged areas in the substructure/subgrade of rail tracks built using conventional ballastless construction methods usually lead to considerable operational restrictions as well as costly construction and maintenance works. If not timely detected, they can jeopardize the operational safety of rail tracks. In this context, the aim of the EPIB 1.1 project was the early detection of local instabilities (so-called muddy spots).

The key procedure of research project EPIB was the elaboration of characteristic properties of punctual instabilities. For this purpose, track measurement data were evaluated and measurements were carried out to be utilized in the determination of track faults. In this case, local instabilities can be detected at an early stage by means of  extracting typical patterns generated from acceleration signals on the axle box in selected simulation scenarios. The knowledge gained can be integrated into track maintenance management through the continuous-monitoring of axle box acceleration with sensors mounted on in-service trains. In this case, a targeted early intervention could be possible, which could help improve the ride comfort, reduce the maintenance costs, increase the service life cylce and better garantie the safety of the track.

The joint project is divided into three subprojects, which were worked on closely together by the institute of Railway and Transportation Engineering (IEV, taking charge of the Subproject EPIB 1.1) and Institute of Geotechnical Engineering (IGS, taking charge of the Subproject EPIB 1.2) of the University of Stuttgart as well as the Chair and Institute of Road, Railway and Airfield Construction of Technical University of Munich (Subproject EPIB 2). The research results of the individual subprojects are presented in separate short final reports and finally a joint final report will be delivered.

See more:  https://gepris.dfg.de/gepris/projekt/321042295

• Determination of characteristic properties of punctual stabilities.
• Collection and evaluation of track defects data coming from the Reallabor
• Detection of punctual instabilities based on typical fault patterns in the axle-box acceleration from the vehicle-track scale model and selected simulation scenarios
• Development of machine learning algorithms for pattern recognition

• Martin, Ullrich; Bahamon-Blanco, Sebastian; Chen, Xiaoyue (2022): Erkennung typi-scher Gleisfehler durch Trägheitsmessungen an einem Modell. In: ETR – Ei-senbahntechnische Rundschau, 71 (2022) 5, Seiten 48 – 51
• Bahamon-Blanco, Sebastian; Liu, Jing; Martin, Ullrich: Convolutional Neural Network for the Early Determination of Local Instabilities. In: Proceedings of IRSA 2021 - 3rd International Railway Symposium, pp. 70 – 81, Aachen, Ger-many, February 2022 https://publications.rwth-aachen.de/rec-ord/841289/files/841289.pdf (reviewed)
• Mitlmeier, Felix; Lillin, Norbert; Kotter, Fabian; Moorman, Christian; Freuden-stein, Stephan; Martin, Ullrich: Frühzeitige Detektion von punktuellen Instabili-täten an Bahnkörpern in konventioneller Schotterbauweise. In: ZEVrail 146 (2022) 03, Seiten 98-104
• Kumawat, A., Martin, U., Bahamon, S., Rapp, S. (2021): The influence of local irregularities on the vehicle-track interaction. In: Tutumluer E., Nazarian S., Al-Qadi I., Qamhia I.I. (eds) Advances in Transportation Geotechnics IV. Lecture Notes in Civil Engineering, vol 165. Springer, Cham. https://doi.org/10.1007/978-3-030-77234-5_20
• Lerke, O., Bahamon-Blanco, S., Metzner, M., Martin, U., Schwieger, V. (2021): Vorarbeiten zur Entwicklung eines Gleisfehlerdetektionssystems mit Regelzügen und Low-Cost Sensorik. ZfV, Vol. 146, No. 3. https://doi.org/10.12902/zfv-0339-2021.
• Bahamon-Blanco, S., Rapp, S., Zhang, Y., Liu, J., Martin, U. (2020): Recognition of Track Defects through Measured Acceleration Using a Recurrent Neural Network. COMPRAIL
• Rapp, S., Martin, U., Strähle, M., Scheffbuch, M. (2019): Track-vehicle scale model for evaluating local track defects detection methods. In: Transportation Geotechnics,
• Bahamon-Blanco, S., Rapp, S., Rupp, C., Liu, J., Martin, U. (2019): Recognition of Track Defects through Measured Acceleration - Part 1&2. The 7th International Conference of Euro Asia Civil Engineering Forum

11.2017 – 04.2020