Axle box acceleration system for condition monitoring of railway tracks

January 11, 2016 in

Postdoc Research by Maria Molodova


Advisor(s)
Maria Molodova

Period
02/01/2014 - 01/20/2016

Theme(s)


Keywords
axle box acceleration, condition monitoring, insulated rail joints,

Partners
ProRail

Funding
TU Delft, ProRail

Link or Download
Not available

Summary

In this project, we worked on a new measuring system for condition monitoring of the railway infrastructure, using axle box acceleration (ABA) measurements. The focus of this study was on assessment of the condition of insulated rail joints (IRJ). IRJs are the core of the signalling system; thus, the failure of IRJs has a direct impact on the safety of the railway track operation.

In the previous work an innovative approach to enhance the sensitivity of the ABA measurements to short wave track defects, particularly squats, by using longitudinal signals was proposed [1, 2], as well as the automatic detection algorithm was developed [3, 4, 5, 6, 7]. To study the applicability of this ABA system to the health monitoring of IRJs, the conditions of a set of real-life IRJs were assessed for different tracks in the Netherlands [8, 9]. IRJs of different quality were included in the study, such as with joints in good condition or with visible surface degradation of varying degrees, IRJs with cracks in the fastening and IRJs with a damaged insulation layer. Subsequently, the ABA responses were analyzed in the time and frequency domains. Based on the results, different indicators were defined to classify the condition of the IRJ, of which the most relevant were certain characteristic frequencies related to the different types of IRJ damage. The proposed indicators were verified using a hammer test.

The application of the results of this study to the health monitoring of IRJs will increase the safety of the railway network and reduce the total yearly IRJ replacement cost by including intelligent preventive maintenance strategies employing the information gathered by this health monitoring system.