The railway track system is a crucial infrastructure for the transportation of people and goods in modern societies. With the increase in railway traffic, the availability of the track for monitoring and maintenance purposes is becoming significantly reduced. Therefore, continuous non-destructive monitoring tools for track diagnoses take on even greater importance. In this context, Ground Penetrating Radar (GPR) technique results yield valuable information on track condition, mainly in the identification of the degradation of its physical and mechanical characteristics caused by subsurface malfunctions. Nevertheless, the application of GPR to assess the ballast condition is a challenging task because the material electromagnetic properties are sensitive to both the ballast grading and water content. This work presents a novel approach, fast and practical for surveying and analysing long sections of transport infrastructure, based mainly on expedite frequency domain analysis of the GPR signal. Examples are presented with the identification of track events, ballast interventions and potential locations of malfunctions. The approach, developed to identify changes in the track infrastructure, allows for a user-friendly visualisation of the track condition, even for GPR non-professionals such as railways engineers, and may further be used to correlate with track geometric parameters. It aims to automatically detect sudden variations in the GPR signals, obtained with successive surveys over long stretches of railway lines, thus providing valuable information in asset management activities of infrastructure managers.

Railway track condition assessment at network level by frequency domain analysis of GPR data / Fontul, Simona; Paixão, André; Solla, Mercedes; Pajewski, Lara. - In: REMOTE SENSING. - ISSN 2072-4292. - STAMPA. - 10:4(2018), pp. 1-26. [10.3390/rs10040559]

Railway track condition assessment at network level by frequency domain analysis of GPR data

Pajewski, Lara
2018

Abstract

The railway track system is a crucial infrastructure for the transportation of people and goods in modern societies. With the increase in railway traffic, the availability of the track for monitoring and maintenance purposes is becoming significantly reduced. Therefore, continuous non-destructive monitoring tools for track diagnoses take on even greater importance. In this context, Ground Penetrating Radar (GPR) technique results yield valuable information on track condition, mainly in the identification of the degradation of its physical and mechanical characteristics caused by subsurface malfunctions. Nevertheless, the application of GPR to assess the ballast condition is a challenging task because the material electromagnetic properties are sensitive to both the ballast grading and water content. This work presents a novel approach, fast and practical for surveying and analysing long sections of transport infrastructure, based mainly on expedite frequency domain analysis of the GPR signal. Examples are presented with the identification of track events, ballast interventions and potential locations of malfunctions. The approach, developed to identify changes in the track infrastructure, allows for a user-friendly visualisation of the track condition, even for GPR non-professionals such as railways engineers, and may further be used to correlate with track geometric parameters. It aims to automatically detect sudden variations in the GPR signals, obtained with successive surveys over long stretches of railway lines, thus providing valuable information in asset management activities of infrastructure managers.
2018
Ground penetrating radar; network level evaluation; railway events; railways; signal frequency analysis; spectral domain; track geometry; earth and planetary sciences (all)
01 Pubblicazione su rivista::01a Articolo in rivista
Railway track condition assessment at network level by frequency domain analysis of GPR data / Fontul, Simona; Paixão, André; Solla, Mercedes; Pajewski, Lara. - In: REMOTE SENSING. - ISSN 2072-4292. - STAMPA. - 10:4(2018), pp. 1-26. [10.3390/rs10040559]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1111354
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