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Structural monitoring for the rail industry using conventional survey, laser scanning and photogrammetry

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Abstract

Monitoring the movement of structures on railway projects in the UK typically involves the fixing of targets (e.g. prisms) or sensors onto the structures being monitored and their surroundings. Whilst this provides discrete point measurement capability across the structure, it is highly intrusive and expensive to setup in a railway environment. Terrestrial laser scanning (TLS) has become an invaluable method of data capture within the surveying industry including applications such as deformation monitoring. The main advantages of TLS, as opposed to other surveying techniques, are the ability to capture large volumes of 3D data at high speed, remotely and with a reasonably high accuracy. A complimentary technique, close-range photogrammetry (CRP), has been traditionally applied to structural monitoring, but is not routinely considered by the railway monitoring community. This technique has the advantage of rapid data capture from a mobile camera with the capability to monitor single points or to generate a point cloud, with an equipment cost approximately twenty times cheaper than a TLS system and at about one tenth the cost of a single instrument total station approach. This paper describes the application of TLS and CRP, along with conventional survey techniques, to the monitoring of a set of masonry arches during a major station refurbishment. Firstly, it investigates the capabilities of using TLS compared to traditional survey methods and encompasses a case where significant movements occur over an extended period of time. Inter-epoch comparison demonstrates a capability to detect change but highlights a requirement to understand the structure and data quality in making valid interpretations. Secondly, the paper compares TLS and CRP techniques as monitoring tools for creating point cloud data on the same set of masonry arches. These investigations generate significant volumes of data conferring the additional challenge of how to visualise observed changes and communicate those changes and their significance to the engineers who must make informed decisions from the data in a timely fashion.

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Notes

  1. http://www.microsurvey.com/products/starnet/

  2. http://www.faro.com/products/faro-software/scene/overview

  3. http://hds.leica-geosystems.com/en/Leica-Cyclone_6515.htm

  4. http://www.ccwu.me/vsfm/

  5. http://www.danielgm.net/cc/

  6. http://geomagic.com/en/products/studio/overview/

  7. http://www.leica-geosystems.co.uk/en/Leica-Nova-MS50_103592.htm

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Acknowledgments

This research is based on a collaborative project funded by the EPSRC (Engineering and Physical Sciences Research Council) and Network Rail through the Virtual Environments Imaging & Visualisation (VEIV) Engineering Doctorate Centre at University College London. The authors would like to thank the survey team at Costain working on the London Bridge Redevelopment Project, in particular Dean Bain and Rob Williams, who organised access to the site and equipment as well as providing continuous support towards the study.

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Correspondence to Anita Soni.

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Soni, A., Robson, S. & Gleeson, B. Structural monitoring for the rail industry using conventional survey, laser scanning and photogrammetry. Appl Geomat 7, 123–138 (2015). https://doi.org/10.1007/s12518-015-0156-1

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