Measurement of three-dimensional velocity profiles using forward-scattering particle image velocimetry (FSPIV) and neural net pattern recognition

Benjie Ovryn, Ted Wright, John D. Khaydarov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

We employ Forward Scattering Particle Image Velocimetry (FSPIV) to measure all three components of the velocity of a buoyant polystyrene particle in oil. Unlike conventional particle image velocimetry (PIV) techniques, FSPIV employs coherent or partially coherent back illumination and collects the forward scattered wavefront; additionally, our field-of-view is microscopic. Using FSPIV, it is possible to easily identify the particle's centroid and to simultaneously obtain the fluid velocity in different planes perpendicular to the viewing direction without changing the collection or imaging optics. We have trained a neural network to identify the scattering pattern as function of displacement along the optical axis (axial defocus) and determine the transverse velocity by tracking the centroid as function of time. We present preliminary results from Mie theory calculations which include the effect of the imaging system. To our knowledge, this is the first work of this kind; preliminary results are encouraging.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsSoyoung S. Cha, James D. Trolinger
Pages112-123
Number of pages12
StatePublished - 1995
Externally publishedYes
EventOptical Techniques in Fluid, Thermal, and Combustion Flow - San Diego, CA, USA
Duration: Jul 10 1995Jul 13 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2546
ISSN (Print)0277-786X

Other

OtherOptical Techniques in Fluid, Thermal, and Combustion Flow
CitySan Diego, CA, USA
Period7/10/957/13/95

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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