Integrated Measurement System for Rapid Shape Measurement, Model Verification and NDE

Abstract

Extensive studies of shape measurement systems have been completed. Both numerical simulations and controlled experiments have been performed. Results have shown that, for fringe patterns having sensor plane fringe spacing from 3 to 30 pixels, the resulting phase error can be reduced to less than 0.02 radians by controlling the spatial frequency of the signal and noise, as well as the contrast in the pattern. Studies of data integration methodologies have also been completed. Results demonstrate that the procedure developed by the authors is both robust and accurate when registering and integrating multiple, overlapped data sets. The effects of key variables in the registration process have been quantified through numerical simulations. Results indicate that when the feature size divided by the overlapped region size, alpha = fs/ls </- 0.5, and the mesh size divided by the feature size, beta = ms/fs </- 0.25, the algorithm can accurately and efficiently register and integrate multiple data sets with a relative error, sigma = ra/ms </- 10%. Finally, studies of automated registration processes have been performed. Local differential geometry properties such as gaussian curvature, K, and mean curvature, H, along with their signs have been used to successfully automate the process of integration of separate shape measurement data sets.

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Document Details

Document Type
Technical Report
Publication Date
Jan 10, 2001
Accession Number
ADA386958

Entities

People

  • Michael A. Sutton

Organizations

  • University of South Carolina

Tags

Communities of Interest

  • Air Platforms
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computer Stereo Vision
  • Computer Vision
  • Curvature
  • Data Sets
  • Databases
  • Differential Geometry
  • Errors
  • Frequency
  • Geometric Forms
  • Geometry
  • Lines (Geometry)
  • Measurement
  • Shape
  • Simulations
  • Three Dimensional

Fields of Study

  • Physics

Readers

  • Approximation Theory.
  • Computational Fluid Dynamics (CFD)
  • Computer Vision.

Technology Areas

  • Space