Login / Signup

Drone-based displacement measurement of infrastructures utilizing phase information.

Shien RiJiaxing YeNobuyuki ToyamaNorihiko Ogura
Published in: Nature communications (2024)
Drone-based inspections provide an efficient and flexible approach to assessing aging infrastructures while prioritizing safety. Here, we present a pioneering framework that employs drone cameras for high-precision displacement measurement and achieves sub-millimeter accuracy, meeting the requirements for on-site inspections. Inspired by the principles of human auditory equilibrium, we have developed an effective scheme using a group of strategical reference markers on the bridge girders to measure structural displacements in the bridge. Our approach integrates the phase-based sampling moiré technique with four degrees-of-freedom geometric modeling to accurately delineate the desired bridge displacements from camera motion-induced displacements. The proposed scheme demonstrates favorable precision with accuracy reaching up to 1/100th of a pixel. Real-world validations further confirmed the reliability and efficiency of this technique, making it a practical tool for bridge displacement measurement. Beyond its current applications, this methodology holds promise as a foundational element in shaping the landscape of future autonomous infrastructure inspection systems.
Keyphrases
  • endothelial cells
  • high glucose
  • high speed
  • molecular dynamics
  • single cell
  • current status
  • diabetic rats
  • machine learning
  • convolutional neural network
  • big data
  • induced pluripotent stem cells
  • artificial intelligence