Light Reflections Detection And Correction For Robotic Volumetric PIV

Abstract

Laser light reflection mitigation in Particle Image Velocimetry (PIV) is
crucial for accurate flow field measurements. While numerous methods
exist for planar PIV, fewer have been developed for volumetric PIV
systems, and in particular for coaxial setups like robotic volumetric
PIV. Light reflections in volumetric PIV experiments result in
high-intensity regions that corrupt particle detection and analysis.
This study presents a novel approach for treating light reflections in
robotic volumetric PIV experiments. The proposed method uses image
filtering and masking techniques in the wavenumber space to separate
particle images from reflection regions. The process involves
decomposing the image signal into low- and high-wavenumber components
using the 2D discrete Fourier transform (DFT) to then use a high-pass
filter to attenuate the intensity of the reflection regions. Finally, a
step of automated adaptive masking is applied to remove residual
reflection areas that the filtering is not able to eliminate. The
proposed approach is tested on experimental data obtained from
experiments performed using robotic volumetric PIV on two different
geometries: a side-view mirror and a rotating two-blade propeller.
Comparison between raw and pre-processed images, as well as particle
tracking results, is presented. The results from this data comparison
show successful removal of reflection-induced artifacts in instantaneous
images by using the spatial Fourier filter automated masking approach.
The developed image pre-processing strategy effectively removes unsteady
light reflection regions in robotic volumetric PIV images, preventing
the appearance of spurious particle tracks and improving the accuracy of
flow field measurements. The spatial gaps introduced by the masking
procedure can be easily filled in via measurements from multiple
directions, which are promptly achieved via the robotic volumetric PIV
approach.