Resumo

William Denner Pires Fonseca, Rafael Franklin Lázaro de Cerqueira, Erick de Moraes Franklin, presented at 26th International Congress of Mechanicel Engineering (COBEM 2021), November 2021.

Abstract

Particle Image Velocimetry (PIV) is a non-intrusive and quantitative technique used for the visualization and measurement of deformation rates in fluid flows. The performance of the PIV technique is determined by the quality of the recorded images and treatment of the data obtained after the acquisition. The PIV technique heavily depends on the quality of the acquired images, i.e., homogeneous lighting, good contrast, low background noise, and suitable particle displacement. However, these conditions cannot always be achieved, and image pre-processing becomes an important tool for an accurate analysis of the problem. In the PIV pre-processing step, the aim is to enhance the correlation signal (displacement peak) and, therefore, produce higher quality vector fields based on contrast improvement, brightness correction, and noise removal. After the pre-processing step, the displacement vector is computed using a PIV correlation algorithm to obtain the velocity field in the next step. This work aims to evaluate and compare the performance of PIV image pre-processing and processing techniques. For this, two types of flows were used, Poiseuille flow and Rankine vortex, created from a PIV image generator and processed using the PIVlab toolbox, both coded in MATLAB. Three image pre-processing methods are analyzed: i) Contrast Limited Adaptive Histogram Equalization (CLAHE); ii) intensity high-pass and; iii) intensity capping. The accuracy of the DCC (Direct-Cross-Correlation) and DFT (Discrete Fourier Transform) algorithms are also evaluated and discussed.