Robustness of railway rolling stock speed calculation using ground vibration measurements

Evaluating railway vehicle speed is an important task for both railway operators and researchers working in the area of vehicle/track dynamics, noise and vibration assessment. The objective of this paper is to present a new technique capable of automatically calculating train speed from vibration sensors placed at short or long distances from the track structure. The procedure combines three separate signal processing techniques to provide high precision speed estimates. In order to present a complete validation, the robustness of the proposed method is evaluate using synthetic railway vibration time histories generated using a previously validated vibration numerical model. A series of simulations are performed, analysing the effect of vehicle speed, singular wheel and rail surface defects, and soil configuration. Virtual conditions of measurement are also examined, taking into account external sources other than trains, and sensor response. It is concluded that the proposed method offers high performance for several train/track/soil arrangements. It is also used to predict train speeds during field trials performed on operational railway lines in Belgium and in UK.