Hostname: page-component-6766d58669-bkrcr Total loading time: 0 Render date: 2026-05-22T02:21:51.150Z Has data issue: false hasContentIssue false
  • English
  • Français

Multi-Cross-Correlation Method in Particle Image Velocimetry

Published online by Cambridge University Press:  31 August 2011

T.-W. Hsu ,
C.-Y. Shin ,
S.-H. Ou  and
Y.-T. Li
T.-W. Hsu*
Affiliation:
Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Tainan, Taiwan 70101, R.O.C.
C.-Y. Shin
Affiliation:
Institute of Ocean Technology and Marine Affairs, National Cheng Kung University, Tainan, Taiwan 70101, R.O.C.
S.-H. Ou
Affiliation:
Department of Environmental Resources Management, Tajen University, Pingtung, Taiwan 90741, R.O.C.
Y.-T. Li
Affiliation:
Institute of Ocean Technology and Marine Affairs, National Cheng Kung University, Tainan, Taiwan 70101, R.O.C.
*
*Professor, corresponding author
Get access

Abstract

A multi-cross-correlation method (MCCM) was developed in a particle image velocimetry (PIV) auto-processing system to reduce spurious vectors and improve accuracy of measurements. This technique is an improvement based on conventional cross-correlation method (CCM). Four typical neighboring interrogation windows were specified to be overlapped and calculated by MCCM. A high cross-correlation value is obtained in which many particle images match up with their corresponding spatially shifted partners, and small cross-correlation peaks due to interference of noises during experiments are reduced. Several parameters such as out-of-plane motions, particle size, and seeding density are considered for checking both MCCM and conventional PIV algorithms. The examination gives authenticity to the merits of MCCM for avoiding particles loss or mistaken velocity vectors.

Keywords

MCCMPIVCross-correlation interrogation method

Information

Type
Articles
Information
Journal of Mechanics , Volume 27 , Issue 3 , September 2011 , pp. 365 - 377
Copyright
Copyright © The Society of Theoretical and Applied Mechanics, R.O.C. 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

REFERENCES

1. Raffel, M, Willert, C, and Kompenhans, J, “Particle Image Velocimetry, a Practical Guide,” Springer, Berlin Heidelberg New York (1998).CrossRefGoogle Scholar
2. Grue, J, Liu, P, and Pedersen, G, “PIV and Water Waves,” Advances in Coastal and Ocean Engineering, 9, World Scientific, Hackensack N.J. London, 352p (2004).CrossRefGoogle Scholar
3. Chang, K, and Liu, P, “Pseudo Turbulence in PIV Breaking-Wave Measurements,” Experiments in Fluids, 29, pp. 331–338 (2000).CrossRefGoogle Scholar
4. Chang, K, Hsu, T, and Liu, P, “Vortex Generation and Evolution in Water Waves Propagating Over a Submerged Rectangular Obstacle, Part II: Cnoidal Waves,” Coastal Engineering, 52, pp. 257–283 (2005).CrossRefGoogle Scholar
5. Keane, R, and Adrain, R, “Optimization of Particle Image Velocimetry, Part I: Double Pulsed Systems,” Measurement Science and Technology, 1, pp. 1202–1215 (1990).CrossRefGoogle Scholar
6. Raffel, M, and Kompenhans, J, “Theoretical and Experimental Aspects of Image-Shifting by Means of a Rotating Mirror System for Particle Image Velocimetry,” Measurement Science and Technology, 6, pp. 795–808 (1995).CrossRefGoogle Scholar
7. Dracos, T, “Three-Dimensional Velocity and Vorticity Measuring and Image Analysis Techniques,” Springer, Berlin Heidelberg New York (1996).CrossRefGoogle Scholar
8. Shavit, U, Lowe, R. J. and Steinbuck, J. V., “Intensity Capping: A Simple Method to Improve Cross-Correlation PIV Results,” Experiments in Fluids, 42, pp. 225–240 (2007).CrossRefGoogle Scholar
9. Keane, R, and Adrain, R, “Theory of Cross-Correlation Analysis of PIV Images,” Applied Scientific Research, 49, pp. 191–215 (1992).CrossRefGoogle Scholar
10. Willert, C, and Gharib, M, “Digital Particle Image Velocimetry,” Experiments in Fluids, 10, pp. 181–193 (1991).CrossRefGoogle Scholar
11. Huang, H, Dabiri, D, and Gharib, M, “On Errors of Digital Particle Image Velocimetry,” Measurement Science and Technology, 8, pp. 1427–1440 (1997).CrossRefGoogle Scholar
12. Westerweel, J, “Efficient Detection of Spurious Vectors in Particle Image Velocimetry Data,” Experiments in Fluids, 16, pp. 236–247 (1994).CrossRefGoogle Scholar
13. Huang, H, Fiedler, H, and Wang, J, “Limitation and Improvement of PIV, Part I: Limitation of Conventional Techniques Due to Deformation of Particle Image Patterns,” Experiments in Fluids, 15, pp. 168–174 (1993a).CrossRefGoogle Scholar
14. Huang, H, Fiedler, H, and Wang, J, “Limitation and Improvement of PIV, Part II: Particle Image Distortion, a Novel Technique,” Experiments in Fluids, 15, pp. 263–273 (1993b).CrossRefGoogle Scholar
15. Veber, P, Dahl, J, and Hermansson, R, “Study of the Phenomena Affecting the Accuracy of a Video-Based Particle Tracking Velocimetry Technique,” Experiments in Fluids, 22, pp. 482–488 (1997).CrossRefGoogle Scholar
16. Yamamoto, F, Wada, A, Iguchi, M, and Ishikawa, M, “Visualization and Image Processing of Torque Converter Internal Flow,” Journal of Flow Visualization Image Proceedings, 3, pp. 51–64 (1996).CrossRefGoogle Scholar
17. Nogueira, J, Lecunoa, A, and Rodriguez, P, “Data Validation, False Vectors Correction and Derived Magnitudes Calculation on PIV Data,” Measurement Science and Technology, 8, pp. 1493–1501 (1997).CrossRefGoogle Scholar
18. Falchi, M, Querzoli, G, and Romano, G. P., “Robust Evaluation of the Dissimilarity Between Interrogation Windows in Image Velocimetry,” Experiments in Fluids, 41, pp. 279–293 (2006).CrossRefGoogle Scholar
19. Brevis, W, Nino, Y, and Jirka, G. H, “Integrating Cross- Correlation and Relaxation Algorithms for Particle Tracking Velocimetry,” Experiments in Fluids, DOI 10.1007/S00348-010-0907-Z. (2010).CrossRefGoogle Scholar
20. Hart, D. P., “PIV Error Correction,” Experiments in Fluids, 29, pp. 13–22 (2000).CrossRefGoogle Scholar
21. Westerweel, J, Digital Particle Image Velocimetry-Theory and Application, PhD Dissertation, Delft University Press, Delft, The Netherlands (1993).Google Scholar
22. Keane, R, Adrian, R, and Zhang, Y, “Super-Resolution Particle Image Velocimetry,” Measurement Science and Technology, 6, pp. 754–768 (1995).CrossRefGoogle Scholar
23. Cowen, E, and Monismith, S, “A Hybrid Digital Particle Tracking Velocimetry Technique,” Experiments in Fluids, 22, pp. 199–211 (1997).CrossRefGoogle Scholar