IN2TRACK3
Research into optimised and future railway Infrastructure 3.
The IN2TRACK3 project is a continuation of IN2TRACK and IN2TRACK2, which will develop physical as well as digital technology and methodology demonstrators for the track, switches and crossings and bridge and tunnel assets. IN2TRACK3 will help to further develop and demonstrate solutions from the previous two projects as well as reduce lifecycle costs, improve the reliability and punctuality of tomorrow's railway.
WP3: Wheel/rail interaction and Simulations and track monitoring
Evaluation of wheel tread measures with its limits for reliable wheel/rail system in order to formulate guidelines that increase availability performance. Investigation of methods to predict and mitigate curve squeal for corves with small radii and validate the results in real context. Perform system prototype demonstration in operational environment for detection of Rolling Contact Fatigue (RCF), especially squats, by sensors e.g. axle box accelerometers. Perform field demonstration in collaboration with Trafikverket.
Test of the sensor Rail Eye: The sensor has been tested in real environments but not mounted on a train. Similar sensors have been mounted on road vehicles with good result. There is a difference between road and rail environment and this is why this sensor need to be tested mounted on a train. The main goal of the test was to investigate how the sensor signals were affected by the motion of the railcar, especially with focus on measuring on the contact band of the rail. In the end of November, the first tests of the Rail eye sensor mounted on a railcar, was carried out. The results looks promising, and when the sensor measured on the contact band of the rail the signals was strong, but when the railcar turned the sensor focus was outside the contact band on the rusty part of the rail the sensor signals went down. This was expected and the development of an upgraded sensor has started. Secondly, the environment close to the rail was not a problem for the sensor, although it was wet and slushy, the sensor handled that fine. If this project is successful, it would enable a sensor that could monitor the rail contamination and top of rail lubrication in real time and produce maps of the current state.
WP5: Bridge health monitoring
Due to the age of the existing railway infrastructure in the world, damage and deterioration of railway bridges is a major social and economic concern in many countries. Therefore, there is a strong need to identify new inspection and monitoring techniques for infrastructure. LTU (for TRV) will lead the work, perform ground-based photogrammetry to create digital models of bridges, develop technology to identify and present changes over time. Outcomes of the project will allow railway infrastructure owners to include this technology as part of their bridge management system.
Sponsors: EU, H2020, SHIFT2RAIL, Trafikverket
Researchers: Jaime Gonzalez, Johan Casselgren, Matti Rantatalo, Florian Thiery, Johan Odelius
Objective: Develop technologies for better assessment and performance of existing railway structures.
Duration: 2021-2023
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