ライブラリ登録: Guest
SJR: 0.161 SNIP: 0.312 CiteScore™: 0.5

ISSN 印刷: 1065-3090
ISSN オンライン: 1940-4336

Journal of Flow Visualization and Image Processing

DOI: 10.1615/JFlowVisImageProc.v24.i1-4.140
pages 215-228

A REVIEW ON THE CROSS-CORRELATION METHODS FOR PIV

Fujio Yamamoto
Faculty of Engineering, University of Fukui, Fukui 910-8507, Japan
Div. of Eng., Aisin AW-Industry Co., Ltd., 38 Ikenokami-cho, Takefu-shi, 915, Japan
Manabu Iguchi
Faculty of Engineering, Osaka University, 2-1 Yamada-oka, Suita-shi, Osaka, 565, Japan
Masa-aki Ishikawa
Fukui University, 3-9-1 Bunkyo, Fukui-shi, 910, Japan

要約

In the image cross-correlation method for the particle imaging velocimetry (PIV acronym), fluid flow velocity vectors are calculated on the grounds of distribution pattern of particle clouds or particle images between two-consecutive pictures using the cross-correlation coefficient. Cross-correlation methods are classified into two types: one is called the brightness distribution method, which uses the equation of cross-correlation defined in the field of primary statistics, and the other is called the binary image method, which uses the equation of cross-correlation devised for the convenience of high-speed calculation without strict mathematical derivation.
This article shows that an exact form of cross-correlation for the brightness distribution method and the conventional equation of cross-correlation for the binary image method can be derived mathematically by using set theory and step function from a general equation defined in an integral form. The characteristics of the two types of cross-correlation methods are discussed based on the derived equations of cross-correlation.
Furthermore, the authors propose a new relation among the correlation parameters of time interval, identification domain size, imaginary particle size, and the velocity gradient tensors in order to raise applicability of the cross-correlation method to any flow fields such as turbulent flows, which include velocity gradient tensors of expansion and compression, shearing, and rotation.

Articles with similar content:

DISCUSSION OF THE CROSS-CORRELATION METHODS FOR PIV
Journal of Flow Visualization and Image Processing, Vol.3, 1996, issue 1
Masa-aki Ishikawa, Manabu Iguchi, Ari-isa Wada, Fujio Yamamoto
CONTRAST ENHANCEMENT IN GRAYSCALE DIGITAL IMAGES APPLYING ATOMIC FUNCTIONS IN FUZZY LOGIC
Telecommunications and Radio Engineering, Vol.72, 2013, issue 19
C. M. Vargas-Martinez, Victor Filippovich Kravchenko, Volodymyr Ponomaryov, Juan Carlos Sanchez-Garcia
Image Compression on the Basis of Edge Compensation in Wavelet Transform
Journal of Automation and Information Sciences, Vol.38, 2006, issue 6
Mikhail G. Lyubarskiy, Vladimir G. Ivanov, Juriy V. Lomonosov
TORQUE CONVERTER INTERNAL FLOW: VISUALIZATION AND IMAGE PROCESSING
Journal of Flow Visualization and Image Processing, Vol.24, 2017, issue 1-4
Masa-aki Ishikawa, Manabu Iguchi, Ari-isa Wada, Fujio Yamamoto
VISUALIZATION AND IMAGE PROCESSING OF TORQUE CONVERTER INTERNAL FLOW
Journal of Flow Visualization and Image Processing, Vol.3, 1996, issue 1
Masa-aki Ishikawa, Manabu Iguchi, Ari-isa Wada, Fujio Yamamoto