Efficient maintenance and monitoring are key points for rolling stocks or railways networks operators. A good knowledge of the structural health and a capability to predict its evolution are main assets to insure a high level of performance. Vibrations and dynamic forces borne by the wheel rail contact contain the main information to reach this objective. Therefore mechanical health features can be deduced from the signal measured on the bogie or on the rail using appropriate data processing algorithms. Moreover the improvements in electronics or communication technologies allow to integrate measurement and data processing functions in an embedded compact system.

The Vibratec wheel rail contact experience leads to consider a cross indirect measurement: a sensor mounted on bogie to monitor the rail and a sensor mounted on rail to monitor the vehicle. Upon this assumption, Vibratec develops a new tool able to detect the defaults and to assess their evolution. To reach the objectives the device must be able to measure vibrations, acoustics, train speed and location, then to process and send the data. A key point is to perform dedicated algorithms to identify and quantify defaults from different origins operating in time domain or in frequency domain.

This paper presents the tests performed with a prototype which includes microphone, accelerometers, magnetic speed sensor and GPS positioning system. The presented results are deduced from measurements carried out on a tramway bogie running on the urban network. The analyse is focused on the rail corrugation, quantified by its roughness and its wavelength. The comparison to the measurements delivered by a corrugation analysis trolley highlight the efficiency of the prototype.