Process control for wheelset machining (PRORAD)

During their lifecycle, train wheels are exposed to extensive load. This results in wear in form of flat spots, local microstructural changes and inclusions on the running surface. To restore the concentricity the profile is reshaped regularly using a turning lathe.

Unpredictable, wear-induced inhomogeneous material properties on the surface can cause process disturbances or even tool failure during machining. Moreover, the variance between different wheels also makes it difficult to determine optimal process parameters.

The objective of this research project is to measure the material properties online during the process. This is done by using a sensor based on the Barkhausen effect to examine the surface. The captured data is used to adapt the machining parameters as cutting speed and feed rate to the individual wheel set.

Additionally, to further optimize process control and monitoring and in particular to detect critical tool wear, an acoustic emission sensor is installed onto the cutting tool. The acoustic emission data is analyzed by considering the material information. The real time processing allows to detect relevant events during the process and to give feedback to the Numerical Control.