Unexpected component wear caused high maintenance costs for rail vehicles and was also the cause of the ICE accident at Eschede. The rupture of a wheel tire due to material fatigue caused 101 deaths and 88 injuries. Today wheel sets for the prevention are tightly controlled, which is associated with high maintenance costs.
The aim of MoSe is the development of a sensor network for the permanent monitoring of the condition of rail vehicles. In the sense of distributed intelligence, a comprehensive human-technology interaction is to be implemented for the evaluation of wear conditions on rail vehicles. The goal is a knowledge-based maintenance planning tool. In addition, a transfer of the results to other fields of application is attempted.
For the development of a sensor network, miniaturized, energy-efficient radio signal detectors are used, which must work reliably in harsh environments. In addition to efficient energy conversion methods ("energy harvesting") and the miniaturized and modular design of the radio signal nodes, the development of algorithms for data evaluation for early wear detection is the core of the project. Based on a cloud, all persons involved should be able to access the wear conditions of the vehicle components at any time.