The Effectiveness of Distributed Acoustic Sensing (DAS) for Broken Rail Detection

Adrian Wagner (), Andrew Nash (), Frank Michelberger, Hirut Grossberger and Gavin Lancaster
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Adrian Wagner: Department of Rail Technology & Mobility, Carl Ritter von Ghega Institute for Integrated Mobility Research, St. Pölten—University of Applied Sciences, Campus Platz 1, 3100 St. Pölten, Austria
Andrew Nash: Department of Rail Technology & Mobility, Carl Ritter von Ghega Institute for Integrated Mobility Research, St. Pölten—University of Applied Sciences, Campus Platz 1, 3100 St. Pölten, Austria
Frank Michelberger: Department of Rail Technology & Mobility, Carl Ritter von Ghega Institute for Integrated Mobility Research, St. Pölten—University of Applied Sciences, Campus Platz 1, 3100 St. Pölten, Austria
Hirut Grossberger: Department of Rail Technology & Mobility, Carl Ritter von Ghega Institute for Integrated Mobility Research, St. Pölten—University of Applied Sciences, Campus Platz 1, 3100 St. Pölten, Austria
Gavin Lancaster: Sensonic GmbH, Bahnhofstraße 57a, 4780 Schärding, Austria

Energies, 2023, vol. 16, issue 1, 1-14

Abstract: Broken rails remain one of the main causes of railway accidents despite improved rail quality and inspections. Today, signalling system with track circuits are often used to detect broken rails, however new signalling systems such as the European Train Control System (ETCS) with axle counters are replacing track circuits and therefore new methods are needed to detect broken rails. One promising technology is distributed acoustic sensing (DAS). The best DAS analytical techniques to show the position of the rail break are gradient analysis, convolution using the train consist and 2 D sinusoidal convolution. This paper describes field tests carried out on DAS to evaluate its ability to detect broken rails and the moment when rails break. The testing showed that DAS has good potential for detecting broken rails in both scenarios. Especially helpful is the ability of DAS to identify the moment of rail breakage and its potential for determining the break’s location on open lines. Recommendations for further research include testing these qualities in more detail and considering how DAS could be efficiently combined with new signalling systems.

Keywords: rail defects; infrastructure; track; vibrations; analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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