A new method to derive rail roughness from axle-box vibration accounting for track stiffness variations and wheel-to-wheel coupling. (1st June 2023) - Carrigan, Tobias D.; Talbot, James P.
Highlights: A new method to derive rail roughness spectra, independent of vehicle speed. Model-based transfer function based on stiffness estimates from the P2 resonance. Improved estimates by accounting for multiple wheels on the same rail. Application of a comb filter to remove the effect of wheel roughness. Evaluation via numerical simulation and measurement trials. Abstract: Railways require frequent inspection to maintain acceptable levels of rail roughness. Accelerometers mounted on in-service railway vehicles potentially offer a cost-effective method of near-continuous roughness monitoring by using a transfer function in the frequency domain to derive rail roughness spectra from measurements of axle-box vibration. This paper addresses two phenomena that currently limit the effectiveness of such a method: the variation in track support stiffness along the track, which is the least known property of the vehicle-track system, resulting in a variable transfer function; and the vibration coupling between wheels, which limits the effectiveness of a transfer function based on a single wheel. A new method is presented that estimates the track stiffness by curve-fitting a transfer function to the peak in the axle-box acceleration spectrum associated with the so-called 'P2' resonance of the wheel-rail system. Wheel-to-wheel coupling is addressed by refining the transfer function to account for multiple wheels running on the same rail. Axle-box acceleration is also affected by wheel roughness, and the use of a comb filter is briefly demonstrated to mitigate this effect. The developments are evaluated by both numerical simulation and measurement trials conducted on London Underground's Victoria line.