21 November 1997 Further evaluation of feature correlation for PIV and PTV
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Abstract
Particle Image Velocimetry and Particle-Tracking Velocimetry have been successfully used for measuring instantaneous velocity fields. Analyzing PIV images involves matching particle images captured sequentially. Correlating interrogation images is commonly used, which determines the non-rotational rigid body motion of interrogation image elements by averaging motions of a sufficient number of particles within the interrogation element. A variety of methods are used for PTV which tracks the motions of individual particles. In PTV applications, particle seeding density is kept low to avoid ambiguity of multiple particles within the interrogation element.PIV allows for higher particle seeking. However, each interrogation element has to be large enough to include a significant number of particles. Both PIV and PTV data processing methods limit the ability of extracting fine spatial scale flow motion from particle image data. The feature-based matching method proposed recently bridges the methods of PIV and PTV. It enables us to track individual particles at higher particle seeding,thus is capable of detecting flow motion at a smaller spatial scale. The feature-based matching method has been evaluated on different data sets. It shows the fine structure of flow field by the motions of each particle and its neighborhoods. Spatially averaged velocity fields are consistent with those calculated from image correlation methods.
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Xin Zhang, Xin Zhang, Charles S. Cox, Charles S. Cox, X. Wang, X. Wang, } "Further evaluation of feature correlation for PIV and PTV", Proc. SPIE 3172, Optical Technology in Fluid, Thermal, and Combustion Flow III, (21 November 1997); doi: 10.1117/12.279750; https://doi.org/10.1117/12.279750
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