Research on PIV algorithm for reconstruction of velocity field of fluid with high Reynolds number

ABSTRACT

For the problems of distortion and rotation in the image matching of turbulent motion with high Reynolds number, according to the nature of affine transformation, using log-polar coordinate transformation, the matching of turbulent particle images is achieved by performing correlation calculations on the image line by line and developed a matching algorithm (Turbulent Particle Image Matching, abbreviation: TPIM) for particle image pairs with affine transformation and rigid body transformation: by moving the interpretation window, the algorithm is no longer restricted by displacements of particles; by setting the affine lines according to the angle of the image in the log-polar coordinate system and using the affine line as the matching unit, the decoupling of different transformation factors is realized; according to the characteristic of non-uniform sampling in log-polar coordinate transformation, based on the principle of not losing image information, by reasonably setting the image mask and the rate of sampling, establishing the image pyramid and the relative coordinate system, the algorithm complexity is reduced to about 15% of the original. The experimental results of various types of particle images show that the matching accuracy of the TPIM algorithm can reach more than 99%.

COEDITOR-IN-CHIEF:

• Yuan, Shyan-Ming

ASSOCIATE EDITOR:

• Jiang, Iris Hui-Ru

KEYWORDS:

• Turbulence
• affine transformation
• particle image velocimetry
• log-polar coordinate transformation
• non-uniform sampling
• relative coordinate system
• image pyramid

Disclosure statement

No potential conflict of interest was reported by the author(s).

Nomenclature

$\mathrm{\Delta }logr$	=	logarithmic distance
$\mathrm{\Delta }\varphi$┘	=	offset of angle
RA	=	resolution of angular after log-polar coordinate transformation
RD	=	resolution of radial distance after log-polar coordinate transformation