Performance improvement of two-frame particle tracking velocimetry using a hybrid adaptive scheme

Abstract

The performance of a two-frame particle tracking velocimetry (PTV) system was enhanced with an adaptive hybrid scheme. he original two-frame PTV method, based on the match probability concept, employs global match parameters for the entire flow field. This does not fully consider the detailed local velocity changes of the flow, and reduces the recovery rate of the velocity vectors, while increasing the number of erroneous vectors in regions of high velocity gradients. In the new hybrid PTV method, the preliminary particle image velocimetry (PIV) results are used to determine the local match parameters that are required for a two-frame particle-tracking algorithm. Both computer simulations and real flow measurements were performed to check the performance of the adaptive hybrid PTV. Compared with the original method, the new technique enhances the PTV performance by increasing the velocity vector recovery rate, while greatly reducing the number of erroneous vectors. In addition, the adaptive hybrid method provides better resolution near solid boundaries compared with the conventional cross-correlation PIV method.