Railway ballast track hanging sleeper defect detection using a smart CNT self-sensing concrete railway sleeper

Abstract

Health monitoring of railway tracks has become an increasingly valuable aspect of railway track maintenance and is taking on a leading role. Considering the current limitations in monitoring of railway components such as ballast and sleepers, a new method of self-sensing smart railway sleeper has been proposed in this research. Carbon nanotubes (CNT) as a functional filler can provide intrinsic self-sensing properties to railway sleepers to detect hanging sleeper defects. Therefore, to analysis the effectiveness of the proposed idea to detect hanging sleeper defect the self-sensing behavior of CNT-cement composite specimens and real scale railway sleepers are studied with three different percentages of CNT as 0.5%, 0.75%, and 1% by cement weight under different support conditions of disturbed and full ballast supports, and different electrode distances. Experimental results show that CNT generates sensitivity for the specimens corresponding to applied loads. This sensitivity is the highest for 0.75 %CNT and 0.5 %CNT and inner electrode distances by 0.043 and 0.036 10-6.N−1. Considering the mechanical performance and sensitivity coefficient (kx), 0.5 %CNT and inner electrodes are the optimal combination of electrode distance and CNT content. FE modeling study shows that hanging defect highly enlarges the dynamic response of hanged sleepers than full support railway sleepers. This increase in dynamic loads due to hanging defect results in hanged sleeper detection using distinguishable sensitivity coefficient values. The kx response in 150 kN axle load is highly relied on train speed as the difference percentage of kx increases by 7% for speed of 100 km/h to 300 km/h.