TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring

In this document an algorithm to detect deformations in the LHC Tunnel of CERN is presented. It is based on two images, one represents the ideal state of the tunnel and the other one the actual state. To find the differences between both, the algorithm is divided in three steps. First, an image enha...

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Autor principal: Fallas, William
Lenguaje:eng
Publicado: 2014
Materias:
Computing and Computers
Engineering
Acceso en línea:http://cds.cern.ch/record/2043823
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author Fallas, William
author_facet Fallas, William
author_sort Fallas, William
collection CERN
description In this document an algorithm to detect deformations in the LHC Tunnel of CERN is presented. It is based on two images, one represents the ideal state of the tunnel and the other one the actual state. To find the differences between both, the algorithm is divided in three steps. First, an image enhancement is applied to make easier the detection. Second, two different approaches to reduce noise are applied to one or both images. And third, it is defined a group of characteristics about the type of deformation desired to detect. Finally, the conclusions show the effectiveness of the algorithm in the experimental results.
id cern-2043823
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2014
record_format invenio
spelling cern-20438232019-09-30T06:29:59Zhttp://cds.cern.ch/record/2043823engFallas, WilliamTunnelVision: LHC Tunnel Photogrammetry System for Structural MonitoringComputing and ComputersEngineeringIn this document an algorithm to detect deformations in the LHC Tunnel of CERN is presented. It is based on two images, one represents the ideal state of the tunnel and the other one the actual state. To find the differences between both, the algorithm is divided in three steps. First, an image enhancement is applied to make easier the detection. Second, two different approaches to reduce noise are applied to one or both images. And third, it is defined a group of characteristics about the type of deformation desired to detect. Finally, the conclusions show the effectiveness of the algorithm in the experimental results.CERN-STUDENTS-Note-2015-025oai:cds.cern.ch:20438232014-08-13
spellingShingle Computing and Computers
Engineering
Fallas, William
TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring
title TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring
title_full TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring
title_fullStr TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring
title_full_unstemmed TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring
title_short TunnelVision: LHC Tunnel Photogrammetry System for Structural Monitoring
title_sort tunnelvision: lhc tunnel photogrammetry system for structural monitoring
topic Computing and Computers
Engineering
url http://cds.cern.ch/record/2043823
work_keys_str_mv AT fallaswilliam tunnelvisionlhctunnelphotogrammetrysystemforstructuralmonitoring

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