Paper
29 September 1995 Fuzzy inference-enhanced information recovery from digital PIV using cross-correlation combined with particle tracking
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Abstract
Particle Image Velocimetry provides a means of measuring the instantaneous 2-component velocity field across the planar region of a seeded flow field. In this work only two camera, single exposure images are considered where both cameras have the same view of the illumination plane. Two competing techniques which yield unambiguous velocity vector direction information have been widely used for reducing the single exposure. multiple image data: cross-correlation and particle tracking. Correlation techniques yiedl averaged velocity estimates over subregions of the flow, whereas particle tracking technique give individual particle velocity estimates. The correlation technique requires identification of the correlation peak on the correlation plane corresponding to the average displacement of particles across the subregion. Noise on the images and particle dropout contribute to spurious peaks on the correlation plane, leading to misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work fuzzy logic techniques are used to determine the true correlation displacement peak even when it is not the maximum peak on the correlation plane, hence maximizing the information recovery from the correlation operation, maintaining the number of independent measurements and minimizing the number of spurious velocity vectors. correlation peaks are correctly identified in both high and low seed density cases. The correlation velocity vector map can then be used as a guide for the particle tracking operation. Again fuzzy logic techniques are used, this time to identify the correct particle image pairings between exposures to determine particle displacements, and thus velocity. The advantage of this technique is the improved spatial resolution which is available from the particle tracking operation. Particle tracking alone may not be possible in the high seed density images typically required for achieving good results from the correlation technique. This two staged approach offers a velocimetric technique capable of measuring particle velocities with high spatial resolution over a broad range of seeding densities.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark P. Wernet "Fuzzy inference-enhanced information recovery from digital PIV using cross-correlation combined with particle tracking", Proc. SPIE 2546, Optical Techniques in Fluid, Thermal, and Combustion Flow, (29 September 1995); https://doi.org/10.1117/12.221509
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Cited by 18 scholarly publications and 1 patent.
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KEYWORDS
Particles

Cameras

Fuzzy logic

Spatial resolution

Particle image velocimetry

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