Multi-Dimensional Analysis of Spatio-Temporal Correlation Information Development of Higher-Order Algorithm of PIV Analysis
The new concept for multi-dimensional PIV analysis of spatio-temporal correlation information is proposed, and the idea was applied to the development of an algorithm for higher-order analysis of multi-frame PIV images. The PIV enabled us to obtain the instantaneous field data of flow velocity, but...
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| Published in | Transactions of Visualization Society of Japan Vol. 29; no. 11; pp. 67 - 75 |
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| Main Authors | , |
| Format | Journal Article |
| Language | Japanese |
| Published |
The Visualization Society of Japan
2009
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1346-5260 1346-5260 |
| DOI | 10.3154/tvsj.29.67 |
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| Abstract | The new concept for multi-dimensional PIV analysis of spatio-temporal correlation information is proposed, and the idea was applied to the development of an algorithm for higher-order analysis of multi-frame PIV images. The PIV enabled us to obtain the instantaneous field data of flow velocity, but the measurement principles remain at the stage of point by point analysis. The authors have proposed utilizing the spatio-temporal sequential image data change, and the field analysis of correlation information was examined. The developed algorithm analyzes the multi-frame correlation information systematically. The correlation information was evaluated by accumulating the correlation information along path lines, and the successive spatio-temporal velocity changes were detected together with its derivatives. The performance of present algorithm was evaluated by means of VSJ standard image. Present approach shows superior performance than the conventional method. |
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| AbstractList | The new concept for multi-dimensional PIV analysis of spatio-temporal correlation information is proposed, and the idea was applied to the development of an algorithm for higher-order analysis of multi-frame PIV images. The PIV enabled us to obtain the instantaneous field data of flow velocity, but the measurement principles remain at the stage of point by point analysis. The authors have proposed utilizing the spatio-temporal sequential image data change, and the field analysis of correlation information was examined. The developed algorithm analyzes the multi-frame correlation information systematically. The correlation information was evaluated by accumulating the correlation information along path lines, and the successive spatio-temporal velocity changes were detected together with its derivatives. The performance of present algorithm was evaluated by means of VSJ standard image. Present approach shows superior performance than the conventional method. The new concept for multi-dimensional PIV analysis of spatio-temporal correlation information is proposed, and the idea was applied to the development of an algorithm for higher-order analysis of multi-frame PIV images. The PIV enabled us to obtain the instantaneous field data of flow velocity, but the measurement principles remain at the stage of point by point analysis. The authors have proposed utilizing the spatio-temporal sequential image data change, and the field analysis of correlation information was examined. The developed algorithm analyzes the multi-frame correlation information systematically. The correlation information was evaluated by accumulating the correlation information along path lines, and the successive spatio-temporal velocity changes were detected together with its derivatives. The performance of present algorithm was evaluated by means of VSJ standard image. Present approach shows superior performance than the conventional method. KW::PIV |
| Author | NISHIO, Shigeru KIRIMOTO, Kensuke |
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| References | 9) やの源亮: トレーサ画像の相関処理による流速計測，流れの可視化，Vol.3, No.10 (1983) pp.189-192. 1) Arroyo, M. P., Greated, C. A.: Stereoscopic particle image velocimetry, Measurement Science and Technology, Vol. 2 (1991) pp.1181-1186. 6) Scarano, F.: Iterative image deformation in PIV, Measurement Science and Technology, Vol.13 (2002) p. R1-R19. 2) Prasad, A. K., Adrian, R. J.: Stereoscopic particle image velocimetry applied to liquid flows, Experiments in Fluids, Vol.15 (1993) pp.40-60. 8) Nishio, S., Kirimoto, K.: Higher-Order Analysis of Correlation Information for Multi-Frame PIV Images, Proceedings of the 6th Pacific Symposium on Flow Visualization and Image Processing, pp.384-389, May 2007, Hawaii, USA. 11) Okamoto, K., Nishio, S., Saga, T., Kobayashi T.: Standard Images for Particle Image Velocimetry, Measurement Science and Technology, 11-6 (2000) pp.685-691. 7) 西尾茂, 岡本孝司: 多時刻粒子画像解析に関する基礎的研究, 可視化情報学会誌, Vol.23, Suppl. No.1 (2003) pp.17-20. 10) Kimura, I.: Image Processing Instrumentation of Flow Velocity Vector Distribution by Using Correlation Technique ; Application to Vortices in the Wake of a Circular Cylinder, Trans. SICE, Vol.23-2 (1987) pp. 101-107. 3) 岡本孝司，佐賀徹雄，西尾茂，小林敏雄: 三次元粒子画像流速測定法（3DPIV），可視化情報学会誌，Vol. 17, No.67 (1997) pp.3-8. 5) Sugii, Y., Nishio, S., Okuno, T., Okamoto, K.: A highly accurate iterative PIV technique using a gradient method, Measurement Science and Technology, Vol.11 (2000) pp. 1666-1673. 4) 西野耕一: 3次元PIVの実用化に向けて，可視化情報学会誌，Vol. 20, No.77 (2000) pp.7-13. |
| References_xml | – reference: 5) Sugii, Y., Nishio, S., Okuno, T., Okamoto, K.: A highly accurate iterative PIV technique using a gradient method, Measurement Science and Technology, Vol.11 (2000) pp. 1666-1673. – reference: 9) やの源亮: トレーサ画像の相関処理による流速計測，流れの可視化，Vol.3, No.10 (1983) pp.189-192. – reference: 10) Kimura, I.: Image Processing Instrumentation of Flow Velocity Vector Distribution by Using Correlation Technique ; Application to Vortices in the Wake of a Circular Cylinder, Trans. SICE, Vol.23-2 (1987) pp. 101-107. – reference: 3) 岡本孝司，佐賀徹雄，西尾茂，小林敏雄: 三次元粒子画像流速測定法（3DPIV），可視化情報学会誌，Vol. 17, No.67 (1997) pp.3-8. – reference: 6) Scarano, F.: Iterative image deformation in PIV, Measurement Science and Technology, Vol.13 (2002) p. R1-R19. – reference: 1) Arroyo, M. P., Greated, C. A.: Stereoscopic particle image velocimetry, Measurement Science and Technology, Vol. 2 (1991) pp.1181-1186. – reference: 11) Okamoto, K., Nishio, S., Saga, T., Kobayashi T.: Standard Images for Particle Image Velocimetry, Measurement Science and Technology, 11-6 (2000) pp.685-691. – reference: 2) Prasad, A. K., Adrian, R. J.: Stereoscopic particle image velocimetry applied to liquid flows, Experiments in Fluids, Vol.15 (1993) pp.40-60. – reference: 7) 西尾茂, 岡本孝司: 多時刻粒子画像解析に関する基礎的研究, 可視化情報学会誌, Vol.23, Suppl. No.1 (2003) pp.17-20. – reference: 8) Nishio, S., Kirimoto, K.: Higher-Order Analysis of Correlation Information for Multi-Frame PIV Images, Proceedings of the 6th Pacific Symposium on Flow Visualization and Image Processing, pp.384-389, May 2007, Hawaii, USA. – reference: 4) 西野耕一: 3次元PIVの実用化に向けて，可視化情報学会誌，Vol. 20, No.77 (2000) pp.7-13. |
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| SubjectTerms | Algorithms Correlation Correlation analysis Correlation information Derivatives Flow velocity Higher-order analysis PIV Spatio-temporal Visualization |
| Subtitle | Development of Higher-Order Algorithm of PIV Analysis |
| Title | Multi-Dimensional Analysis of Spatio-Temporal Correlation Information |
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