Particle Selection Strategy for Three-Dimensional Particle Image Velocimetry

When matching between two image frames with interrogation windows, the correlation result only presents a local average value instead of the result of a point. So the processing is with lower resolution. In order to improve the processing resolution, a new particle selection strategy in PIV is presented. Firstly, the vector at current position is detected. Secondly, the contribution of particles in the matching field is evaluated. According to the evaluation results, particles at different positions are estimated using the rigid motion hypothesis. Then, the uniqueness of global vectors is estimated. Finally, synthetic particle images are tested using the proposed algorithm and the errors are analyzed. The experimental results show that the proposed method has large improvements in analysis precision.