Spatial pyramidal cross correlation for particle image velocimetry |
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| Authors: | HongPing Wang Peng Wu Qi Gao JianJie Wang JinJun Wang |
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| Affiliation: | 1.Key Laboratory of Fluid Mechanics, Ministry of Education,Beihang University,Beijing,China;2.State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics,Chinese Academy of Sciences,Beijing,China;3.Artificial Organ Technology Laboratory, Biomanufacturing Centre, School of Mechanical and Electrical Engineering,Soochow University,Suzhou,China |
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| Abstract: | A spatial pyramidal cross-correlation based on interrogation area sub-division is introduced to improve the measurement resolution in particle image velocimetry (PIV). The high-resolution velocity can be achieved with a velocity prediction model via coarse cross-correlation. The prediction formula is deduced from the frequency response of the moving average (MA). The performance of this method was assessed using synthetically generated images of sinusoidal shear flow, two-dimensional vortical cellular flow, and homogeneous turbulence. A real PIV experiment of turbulent boundary layer was used to evaluate the new method. The results indicate that the spatial pyramid cross-correlation can robustly increase the spatial resolution. |
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