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Non-contact monitoring of railway infrastructure with terrestrial laser scanning and photogrammetry at Network Rail

Soni, A; (2016) Non-contact monitoring of railway infrastructure with terrestrial laser scanning and photogrammetry at Network Rail. Doctoral thesis , UCL (University College London). Green open access

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Abstract

Current monitoring practices in the railway industry primarily rely on total station and prism based methods. This approach requires the installation and maintenance of prisms directly onto the structure being monitored which can be invasive and expensive. This thesis presents the outcomes of an industrial based doctorate, motivated by the Network Rail Thameslink Programme, to investigate the potential of terrestrial laser scanning and photogrammetry as an alternative non-contact and “target-less” solution to monitoring railway infrastructure. The contributions made by this thesis in the context of Network Rail requirements include: a laboratory based exploration of the state of the art in target and surface-based measurements; a validation of conventional, terrestrial laser scan and photogrammetric surveys of a deforming set of brick arches; and a novel prism-less method of track measurement using terrestrial laser scanner data. The complete project has been carried out as part of the highly complex and dynamic £900m London Bridge Redevelopment Project. The thesis comprises of a review of existing monitoring system performance and highlights challenges in the adoption of this technology through interviews of leading professionals in the monitoring industry. Laboratory tests utilise network adjustment prediction and analysis to compare state of the art total station, terrestrial laser scanning and close-range photogrammetry instrumentation to both target and target-less deformation monitoring scenarios. The developed tests allow the performance of each technique to be assessed within the context of state of the art and Network Rail operational practice and are extensible to developments in each of these technologies. Results demonstrate performances to sub-millimetre level and are validated through the use of a Leica AT401 laser tracker. Each technique is then explored within the London Bridge Redevelopment Project through a series of live monitoring sites where their ability to either augment or replace existing survey techniques is evaluated. Results from the on-site monitoring of historic brick arch structures demonstrate surface measurements compatibility at the millimetre level, highlighting close agreement between instrument performance established in the laboratory. A key use of prism-based techniques is in the determination of engineering track parameters where costly prism systems, both in terms of installation and subsequent maintenance, attached to the track are a key concern. Here laboratory validated track surface measurement, with terrestrial laser scanning, has been deployed on a 15 metre long dual track site and shown to be highly capable of replacing prism systems for the determination of accurate track geometry. This work has included a novel optical non-contact measurement process utilising individual rail cross section designs to automatically extract relevant track geometry parameters within 1mm of prism-based methods. The method offers excellent potential for incorporation into an automated track monitoring system. Outcomes from the thesis have been published in peer-reviewed journals and conferences.

Type: Thesis (Doctoral)
Title: Non-contact monitoring of railway infrastructure with terrestrial laser scanning and photogrammetry at Network Rail
Event: UCL
Open access status: An open access version is available from UCL Discovery
Language: English
Keywords: structural monitoring, terrestrial laser scanning, photogrammetry, railway
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1477352
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