The present work introduces an extension to three-dimensional Particle Tracking Velocimetry (3-D PTV) in order to investigate small-scale flow patterns. Instead of using monochrome particles the novelty over the prior state of the art is the use of differently dyed tracer particles and the identification of particle color classes directly on Bayer raw images.
Especially in the case of a three camera setup it will be shown that the number of ambiguities is dramatically decreased when searching for homologous points in different images. This refers particularly to the determination of spatial particle positions and possibly to the linking of positions into trajectories. The approach allows the handling of tracer particles in high numbers and is therefore perfectly suited for gas flow investigations. Although the idea is simple, difficultties may arise particularly in determining the color class of individual particle when its projection on a
This work describes an original approach for 3D Particle Tracking Velocimetry (3D PTV), applicable also for gaseous flows and based on tracer particles of different colours. On the images acquired by several cameras, tracer particles are handled by colour recognition and 3D localisation. Then, the PTV tracking algorithm rebuilds the trajectories of the tracer particles using a criterion of Minimum Acceleration. Theoretical and numerical calculations are first presented to demonstrate that the employed coloured tracer particles follow in a suitable manner the considered gas flows. The test cases analysed comprise low Reynolds number flows involving a variety of interesting features, in particular boundary layer separation, continuous acceleration and recirculations. The experimental setup and the 3D PTV procedure are then described. All results are analysed in a quantitative manner and demonstrate the performance of the developed measurement strategy in gas flows.
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