Advances in iterative multigrid PIV image processing

Abstract

An image-processing technique is proposed, which performs iterative interrogation of particle image velocimetry (PIV) recordings. The method is based on cross-correlation, enhancing the matching performances by means of a relative transformation between the interrogation areas. On the basis of an iterative prediction of the tracers motion, window offset and deformation are applied, accounting for the local deformation of the fluid continuum. In addition, progressive grid refinement is applied in order to maximise the spatial resolution. The performances of the method are analysed and compared with the conventional cross correlation with and without the effect of a window discrete offset. The assessment of performance through synthetic PIV images shows that a remarkable improvement can be obtained in terms of precision and dynamic range. Moreover, peak-locking effects do not affect the method in practice. The velocity gradient range accessed with the application of a relative window deformation (linear approximation) is significantly enlarged, as confirmed in the experimental results.