  The railpad is a key element in railway infrastructures that plays an
essential role in the train-track dynamics. Presence of worn or defective
railpads along railway track may lead to large wheel/rail interaction forces,
and a high rate of deterioration for track components. Despite the importance
of railpad, the track infrastructure managers use no inspection tool for
monitoring in-service railpads over time. In this paper, a novel data-driven
monitoring tool for long-term performance analysis of in-service railpads is
developed based on train-induced vibration data collected by a track-side
measurement system. The monitoring tool consists of a method for track
resonance frequencies estimation, a temperature-frequency model for describing
railpad behavior with respect to ambient temperature, and a generalized
likelihood ratio test based on the generalized extreme value distribution for
detecting changes in the railpad status over time. To evaluate the performance
of the proposed monitoring system, the status of railpads at four different
locations along a railway turnout is monitored over a period of 18 months. It
is shown that the monitoring system can successfully detect changes in railpad
properties over the considered period.
