Affiliations: Laboratoire Traitement du Signal et Instrumentation,
URA CNRS No. 842 Université Jean Monnet, 23, rue du docteur Paul
Michelon 42023 Saint-Etienne Cedex, France. | Centre de Thermique, INSA Lyon, URA CNRS 1372,
batiment 404, 20, avenue Albert Einstein 69621 Villeurbanne Cedex,
France.
Abstract: An algorithm is presented to determine displacements thanks to the
identification method. Its main properties are described: no link with the
particle size, measurement of the velocity distribution. Determination of
effects of PIV parameters on displacement identification is made. Parameters
used are noise, bias, velocity distribution. Therefore, we can define a
validity domain of PIV parameters for identification and compare it with the
domain of cross correlation. The identification validity range is based on 70%
of isolated particles, on a displacement norm and on displacement gradients
corresponding to less than half the size of the interrogation cell and to 10%
of the average velocity. The comparison with cross correlation domains
indicates that the cross correlation is more robust. However, the
identification method is interesting because of the possibility of displacement
distribution measurement. We use it to measure the decreasing of the turbulence
intensity for a grid-generated turbulence.
Keywords: particle image velocimetry, identification, displacement, signal to noise ratio