Improvements in Axle Box Acceleration Measurements for the Detection of Light Squats in Railway Infrastructure

Abstract

Squats are a type of short-wave rolling contact fatigue defect whose early detection can contribute to cost reductions in the railway industry. This paper demonstrates how the early detection of squats is possible via enhanced instrumentation based on axle box acceleration (ABA) and adequate postprocessing. Three improvements are discussed. The first corresponds to the use of longitudinal ABA to enhance measurement sensitivity to light squats. Compared to vertical ABA, longitudinal ABA does not contain the vibrations of the rail, fastening, sleepers, and ballast, and thus, the impact-related vibration is considerably stronger in the signal. The second improvement considers the use of multiple sensors, noise-reduction techniques, and repeated measurements. Due to hunting, the wheels of a measuring train do not always pass over small squats; thus, light squats are more likely to be detected using multiple sensors and multiple measurement runs. The third improvement concerns the signal-processing solution for the reduction of disturbances from wheel defects. Extensive field measurements show that these improvements make the characteristics of squats more visible in signals and allow the squats to be distinguished from vibrations of other origins.