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Virginia Tech

Improving the Three Dimensional, Structural Velocity Field Reconstruction Process with Computer Vision

Abstract

dc:description.abstract

This research presents improvements to the velocity field reconstruction process achieved through computer vision. The first improvement of the velocity reconstruction process is the automation of the scanning laser Doppler vibrometer (SLDV) pose procedure. This automated process results in superior estimates of the position and orientation of the SLDV. The second improvement is the refinement of the formulation for reconstruction of the velocity field. The refined formulation permits faster computation, evaluation, and interpretation of the reconstructed structural velocity field. Taken together, these new procedures significantly improve the overall velocity reconstruction process which results in better, unbiased out-of-plane velocity estimates in the presence of noise. The automation of the SLDV pose procedure is achieved through a computer vision model of the SLDV. The SLDV is modeled as a projective camera, i.e. an imager which preserves projectivities. This projective camera model permits the precise association of object features with image features. Specifically, circular features in the object space are seen by the SLDV as ellipses in the image space. In order to extract object points, the bitangents among the circular features are constructed and the bitangent points selected. The accuracy and precision of the object points are improved through the use of a calibrated object whose circular features are measured with a coordinate measuring machine. The corresponding image points are determined by constructing the bitangents among the ellipses and selecting the tangent points. Taken together, these object/image bitangent point sets are a significantly improved data set for previously developed SLDV pose algorithms. Experimental verification of this automated pose procedure includes demonstrated repeatability, independent validation of the estimated pose parameters, and comparison of the estimated poses with previous methods. The refinement of the velocity reconstruction formulation is a direct result of the computer vision viewpoint adapted for this research. By viewing the velocity data as images of the harmonically excited structure's velocity field, analytical techniques developed for holographic interferometry are extended and applied to SLDV velocity images. Specifically, the "absolute" and "relative" fringe-order methods are used to reconstruct the velocity field with the "best" set of bases. Full and partial least squares solutions with experimental velocity data are calculated. Statistical confidence bounds of the regressed velocity coefficients are analyzed and interpreted to reveal accurate out-of-plane, but poor in-plane velocity estimates. Additionally, the reconstruction process is extended to recover the velocity field of a family of surfaces in the neighborhood of the "real" surface. This refinement relaxes the need for the exact experimental geometry. Finally, the velocity reconstruction procedure is reformulated so that independent least squares solutions are obtained for the two in-plane directions and the out-of plane direction. This formulation divides the original least squares problem into three smaller problems which can be analyzed and interpreted separately. These refinements to the velocity reconstruction process significantly improve the out-of-plane velocity solution and interpretation of the regressed velocity parameters.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Mechanical Engineering
Department dc:contributor.department
Mechanical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
1998

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Coe, David Hazen
Chair dc:contributor.committeechair
  • West, Robert L. Jr.
Committee members dc:contributor.committeemember
  • Mitchell, Larry D.
  • Farkas, Daniel R.
  • Abbott, A. Lynn
  • Reinholtz, Charles F.

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-8998-163252
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/30742

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Coe, David Hazen. Improving the Three Dimensional, Structural Velocity Field Reconstruction Process with Computer Vision. doctoral thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/30742