Railway Track Condition Assessment at Network Level by Frequency Domain Analysis of GPR Data

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Fontul, S (Author) Other; Paixao, A (Author) FEUP; Solla, M (Author) Other; Pajewski, L (Author) Other

Journal

Title: Remote Sensing

Vol. 10

Final page: 559

ISSN: 2072-4292

Publisher: MDPI

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Other information

Authenticus ID: P-00N-XGR

DOI: 10.3390/rs10040559

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 26