Strain monitoring strategy of deformed membrane cover using unmanned aerial vehicle-assisted 3D photogrammetry

Benjamin Steven Vien, Leslie Wong, Thomas Kuen, Frank Courtney, Jayantha Kodikara, Wing Kong Chiu

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Large structures and high-value assets require inspection and integrity assessment methodologies that ensure maximum availability and operational capabilities. Large membranes are used as floating covers at the anaerobic wastewater lagoons of MelbourneWater'sWestern Treatment Plant (WTP). A critical function of this high-value asset pertains to the harnessing of the biogas gas generated at these lagoons as well as protecting the environment from the release of odours and greenhouse gases. Therefore, a proactive inspection and efficient management strategy are required to ensure these expensive covers' integrity and continued operation. Not only is identifying the state of stress on the floating cover crucial for its structural integrity assessment, but the development of rapid and non-contact inspections will significantly assist in determining the "real-life" performance of the cover for superior maintenance management. This study investigates a strain determination method for WTP floating cover which integrates unmanned aerial vehicle (UAV)-assisted photogrammetry with finite element analyses to determine the structural integrity of these covers. Collective aerial images were compiled to form 3D digital models of the deformed cover specimens, which were then employed in computational and statistical analyses to assess and predict the strain of the cover. The findings complement the future implementation of UAV-assisted aerial photogrammetry for structural health assessment of the large floating covers.

Original languageEnglish
Article number2738
Number of pages21
JournalRemote Sensing
Volume12
Issue number17
DOIs
Publication statusPublished - 1 Sep 2020

Keywords

  • 3D scanning
  • Membrane
  • Photogrammetry
  • Strain determination
  • Structural health monitoring
  • Unmanned aerial vehicle

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