Toggle Main Menu Toggle Search

Open Access padlockePrints

T-Vision: A hybrid subsurface radar inspection system for intelligent asset management of railway tunnels

Lookup NU author(s): Thomas McDonaldORCiD, Professor Gui Yun TianORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

As global rail network demand grows and historic tunnels continue to age, it is vital to detect Hidden Critical Elements (HCEs) – e.g. blind shafts and ring separation – in Rail Tunnel Subsurface Inspection (RTSSI) surveys to maintain safe and efficient network operation. Presently, no standalone RTSSI technology can swiftly nor accurately detect HCEs throughout a 3600 tunnel subsurface profile. In response, our European research project T-Vision investigates and proves the feasibility of the first air-launched, hybrid rotational ground penetrating radar system for RTSSI. We deploy the system's unique raster and helical scanning functionality in Kirton Tunnel (UK) to inspect the subsurface. Artefacts corresponding to blind shafts validate raster scanning efficacy for concealed shaft detection; whilst development scope for novel 3600 Hackle-Helix Point Clouds for RTSSI is discussed.


Publication metadata

Author(s): McDonald T, Robinson M, Tian G

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Transport Research Arena 2022

Year of Conference: 2022

Pages: 3466-3473

Print publication date: 13/12/2023

Online publication date: 13/12/2023

Acceptance date: 12/06/2022

Date deposited: 22/08/2024

ISSN: 2352-1465

Publisher: Elsevier

URL: https://doi.org/10.1016/j.trpro.2023.11.768

DOI: 10.1016/j.trpro.2023.11.768

Series Title: Transportation Research Procedia


Share