A Simulation Study on Characterizing Transfer Functions of Railway Tracks Using Train-Borne Laser Doppler Vibrometer

Abstract

Due to train load and aging, the dynamic properties of railway tracks degrade over time and deviate over space, which should be monitored to facilitate track maintenance decisions. A train-borne laser Doppler vibrometer (LDV) can directly measure track vibrations in response to the moving train load, which can be potentially applied to large-scale rail infrastructure monitoring. This paper characterizes track structures as a distributed system by estimating transfer functions between the wheel-rail force and the response of each sleeper measured by a train-borne LDV. A challenge with this technique is that a train-borne LDV measures only a fragment of the response for each sleeper while the train load is moving. To investigate the feasibility of this technique and the influence of key factors, we perform numerical simulations using a vehicle-track model and analyze the estimation performance through comparison with simulated impact hammer tests. We find that the transfer function estimated under a moving excitation is close to but noisier than that estimated under an impact load. Partial measurement affects the estimation performance significantly, and a wider sleeper provides a better estimate and a higher frequency resolution. Train speed is a crucial factor for a train-borne LDV system. As the vehicle speed increases, the estimation performance gets better at high frequencies but worse at low frequencies.