3-D advanced gas-cooled nuclear reactor fuel channel reconstruction using structure-from-motion

Kristofer Law, Graeme West, Paul Murray, Chris Lynch

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)
114 Downloads (Pure)

Abstract

During planned, periodic outages, a selection of fuel channels within the UK fleet of Advanced Gas-cooled Reactor (AGR) cores are inspected using specialist tools which record video footage and other sensory data for each channel which undergoes inspection. Current visualization techniques comprise of manually produced montages by inspection engineers of points of interest (i.e. structural defects) and 2-D panoramic images of the fuel channels automatically produced using bespoke image stitching software. Both techniques however provide limited structural information due to the loss of depth data as a result of the image formation process. By recovering the depth information from the footage, a 3-D model could be constructed and subsequently, allow for more accurate profiling of specific defects observed during inspection in addition to obtaining the fuel channels structure using existing footage. This work explores the preliminary application of a 3-D visualization technique known as Structure-from-Motion (SfM) which aims to obtain 3-D information by exploiting image correspondences across multiple viewpoints of the same scene in the RVI footage. This paper investigates the difficulties of applying state-of-the-art SfM to RVI footage and we present new techniques to improve feature correspondence searching in repetitive, non-descript environments.
Original languageEnglish
Number of pages10
Publication statusPublished - 11 Jun 2017
Event10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 - Hyatt Regency, San Francisco, United States
Duration: 11 Jun 201715 Jun 2017
http://npic-hmit2017.org/

Conference

Conference10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
Abbreviated titleNPIC and HMIT 2017
Country/TerritoryUnited States
CitySan Francisco
Period11/06/1715/06/17
Internet address

Keywords

  • visual inspection
  • Structure-from-Motion
  • Image processing
  • feature detection

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