An innovative approach to continuously monitor rail track surface displacement during freezing-thawing seasons

Abstract

Large differential displacement as a result of freeze–thaw cycles (FTC) is a major issue affecting the safety and performance of railway tracks constructed in cold regions. Current track monitoring methods in winter are mainly based on visual inspection and manual measurements. The frequency of FTC is expected to increase under future climate and thus it is essential for railway operators to employ new methods of inspection that allow continuous and remote monitoring of railway tracks during the freeze–thaw period. While sensors are commonly used to measure localized track displacement, the advantages and limitations of using instruments that are capable of collecting data over a segment of track is not well understood. This paper investigates the use of a micro electro-mechanical sensor (MEMS) based instrument for monitoring surface displacement of railway tracks during FTC. The ShapeArray™ instrument, in this case the SAAX inclinometer, is a MEMS based sensor that was selected due to its ability to collect data over a segment of track (up to 150 m). Two sets of SAAX inclinometers were installed on a 50-metre section of track to measure data during two freezing-thawing periods. Analysis of the field data suggests that the main limitation of using MEMS-based sensors is their sensitivity to fluctuations of ambient temperature which may be confused with their responses to actual track displacement. A data analysis technique has been developed to remove the unwanted variations so that the instrument can be effectively used for monitoring track displacement during FTC. The comparison of the processed measurements with data collected from a digital level suggested that it provides a reasonably accurate measure of track surface displacement. Overall, the limited investigations in this project suggests that using MEMS-based sensor along with proper data processing techniques can provide useful information about the differential displacement over a segment of track, a key parameter for the safety of railway operation. The measurements can also be transferred through the cloud, enabling track engineers to remotely monitor track condition in near-real-time without the need to access the track and interrupt trains operations.