In this paper, we propose a newPIV methodology for obtaining a velocity field from a sequence of multiple image data based on a least-square principle (also known as MQD ; minimum quadratic difference) for the grey level difference between two neighboring frames of image data. We investigated both the accuracy of the result and the time consumption in the computation. It turns out that the proposed method is not only accurate but fast compared with the conventional correlationPIV techniques. Our method is applied to the spin-up flows and the results show that the method can be a good substitution for the conventional algorithms employed in the existing commercial codes.
Key WordsMQD (Minimum Quadratic Difference)PIV. Least-Square Principle Multi-Frame PIV Cross-Correlation Spin-Up Flow
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- Beebe, D. J., Adrian, R. J., Olsen, M. G., Stremler, M.A., Aref, H. and Jo, B. H., 2001, “Passive Mixing in Microchannels,”Mec. Ind., Vol. 2, pp. 343–348.Google Scholar
- Chetelat, O., Yoon, S. Y. and Kim, K. C., 2001, “Design and Construction of a Miniature PIV (MPIV) System,”KSME Int. J., Vol. 15, No. 12, pp. 1775–1783.Google Scholar
- Liu, R. H., Stremler, M. A., Sharp, K. V., Olsen, M. G., Santiago, J. G., Adrian, R. J., Aref, H. and Beebe, D. J., 2000, “Passive Mixing in a Three Dimensional Serpentine MicroChannel,”J. MEMS, Vol. 9, No. 2, pp. 190–197.Google Scholar
- Raffel, M., Willert, C. and Kompenhans. J., 1999,Particle Image Velocimetry, Springer-Verlag.Google Scholar