This study proposes a track condition monitoring technique using car-body acceleration that can be easily measured by an in-service vehicle for the sake of an increase in safety of railway transportation. This paper demonstrates the possibility of estimating track irregularities of conventional railway tracks using car-body acceleration only. The methodology proposed uses inverse dynamics to estimate track irregularity from car-body acceleration, applying a Kalman filter to solve this problem. This technique estimates the track irregularity in the longitudinal plane (track geometry and 10m-chord versine). The Kalman filter is able to apply to inverse analysis by expressing track geometry as a random walk model, and incorporating the model in an equation of state. The estimation technique can support a change of the vehicle velocity by selecting an appropriate impulse response in the measurement equation for the vehicle velocity. Estimation results in simulation and full scale tests revealed that the proposed estimation technique is effective for track condition monitoring with acceptable accuracy for conventional railways.

In-service vehicles equipped with sensors and GNSS systems can act as probes to detect and analyse real-time vehicle vibration. A compact on-board sensing device has been developed and used for the track condition monitoring system. The diagnosis software provides the function of detecting track faults using the root mean square (RMS) of the car-body acceleration. It also permits analysis in the time-frequency domain using wavelet transform. The actual measured data were obtained from regional railway lines using the developed track condition monitoring system. The degradation level of tracks has been monitored by the system developed and fed back to railway operators to inform on a track maintenance scheme. Field test results in regional railway lines showed that the system is effective for preventive maintenance work.