Development of a Machine Learning Method to Calculate Real-time 3D Deflections in a Dynamic Magnetic Field
Trelleborg is developing a contactless 3D deflection measuring system. The system allows capturing static and dynamic deflections as a basis for complex condition monitoring and predictive maintenance approaches – especially in railway applications.
The task contains:
- Development of a Machine Learning model which is able to infer 3D deflections by combining different sensor signals
- Gaining knowledge of the physical system behavior as well as correlations in the sensor values
- Validating approach on laboratory tests and benchmarks
- First prototype of sensor hardware available and tested
- Extensive datasets for analysis available
- Improved sensor hardware available in 08/2019
- First approach of algorithm as base for improvements / benchmarking
- Wide range of tools and hardware for additional tests available
- Real-time capable prediction model / algorithm
- Measuring accuracy of 0.1 mm
- Development of proper calibration and commissioning processes
If you are interested, send a short letter of motivation, your CV and a transcript of records to dominik.martin∂kit.edu.