한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제54권11호
  • /
  • Pages.933-942
  • /
  • 2021
  • /
  • 2799-8746(pISSN)
  • /
  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
권호 표지
DOI QR코드

DOI QR Code

고속푸리에변환을 이용한 시공간 체적 표면유속 산정 기법 개발

Calculation of surface image velocity fields by analyzing spatio-temporal volumes with the fast Fourier transform

  • 류권규 (동의대학교 토목공학과) ;
  • 유병호 (동의대학교 토목공학과 (중국 호남공업대학교))
  • Yu, Kwonkyu (Department of Civil Engineering, Dong-eui University) ;
  • Liu, Binghao (Department of Civil Engineering, Dong-eui University (Department of Civil Engineering, Hunan Institute of Engineering))
  • 투고 : 2021.06.21
  • 심사 : 2021.09.30
  • 발행 : 2021.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

홍수시 하천의 유속을 효율적이고 안전하게 측정할 수 있는 방법의 하나로 제시된 것이 표면 영상유속측정법이다. 표면영상유속측정법에는 영상분석 기법에 따라 다양한 종류가 있으나, 이 중에서도 최근 일정시간 동안의 유속의 시간평균을 한 번에 산정할 수 있는 시공간영상 유속계측법이 하천의 표면유속 측정에 대한 연구가 활발히 진행되고 있다. 시공간영상 유속계측법은 일정 시간 동안의 시공간 영상을 한 번에 분석하기 때문에, 유속산정 시간을 획기적으로 줄일 수 있는 장점이 있다. 그러나 시공간영상 유속계측법은 주흐름방향을 정확히 알지 못하면 오차를 유발할 수 있다. 본 연구는 표면영상을 시간적으로 누적한 시공간체적을 구성하고, 이 시공간체적에서 시간축 방향으로 최대값 영상을 만든 뒤 이를 고속푸리에변환하여 주흐름방향을 탐색하는 새로운 기법을 제안하였다. 이 방법은 공간영상에서 주흐름방향을 찾는 첫단계와 주흐름방향의 시공간영상에서 유속의 크기를 산정하는 두번째 단계로 구성되어 있다. 첫번째 단계에서 찾아낸 주흐름방향으로 시공간영상을 작성하고, 이 시공간영상의 고속푸리에변환을 이용하여 유속을 산정하였다. 제안된 방법은 주흐름방향을 정확하게 추정하여 시공간영상을 생성하고 분석하므로, 기존 방법들이 취약했던 이차원 흐름에 대해서도 신속하고 정확한 유속분석이 가능하다. 개발된 방법을 공동흐름에 대한 인공영상에 적용한 결과 비교적 정확하게 2차원 유속분포 측정이 가능한 것으로 나타났다.

The surface image velocimetry was developed to measure river flow velocity safely and effectively in flood season. There are a couple of methods in the surface image velocimetry. Among them the spatio-temporal image velocimetry is in the spotlight, since it can estimate mean velocity for a period of time. For the spatio-temporal image velocimetry analyzes a series of images all at once, it can reduce analyzing time so much. It, however, has a little drawback to find out the main flow direction. If the direction of spatio-temporal image does not coincide to the main flow direction, it may cause singnificant error in velocity. The present study aims to propose a new method to find out the main flow direction by using a fast Fourier transform(FFT) to a spatio-temporal (image) volume, which were constructed by accumulating the river surface images along the time direction. The method consists of two steps; the first step for finding main flow direction in space image and the second step for calculating the velocity magnitude in main flow direction in spatio-temporal image. In the first step a time-accumulated image was made from the spatio-temporal volume along the time direction. We analyzed this time-accumulated image by using FFT and figured out the main flow direction from the transformed image. Then a spatio-temporal image in main flow direction was extracted from the spatio-temporal volume. Once again, the spatio-temporal image was analyzed by FFT and velocity magnitudes were calculated from the transformed image. The proposed method was applied to a series of artificial images for error analysis. It was shown that the proposed method could analyze two-dimensional flow field with fairly good accuracy.

키워드

과제정보

이 연구는 낙동강수계관리위원회 환경기초조사사업의 지원을 받아 추진되었습니다. 지원에 감사드립니다.

참고문헌

  1. Aya, S., Fujita, I., and Yagyu, M. (1995). "Field-observation of flood in a river by video image analysis." Annual Journal of Hydraulic Engineering, JSCE, Vol. 39, pp.447-452. (in Japanese) https://doi.org/10.2208/prohe.39.447
  2. Bae, I., Yu, K., Yoon, B., and Kim, S. (2017). "A study on the applicability of invisible environment of surface image velocimeter using far infrared camera." Journal of Korea Water Resources Association, Vol. 50, No. 9, pp. 597-607. (in Korean) https://doi.org/10.3741/JKWRA.2017.50.9.597
  3. Bigun, J. (2006). Vision with direction - a systematic introduction to image processing and computer vision. Springer, Berlin, Germany.
  4. Burger, W., and Burge, M.J. (2016). Digital image processing: An introduction using Java. second ed., Springer, Berlin, Germany.
  5. Ettema, R., Fujita, I., Muste, M., and Kruger, A. (1997). "Particle-image velocimetry for whole-field measurement of ice velocities." Cold Regions Science and Technology, Vol. 26, No. 2, pp. 97-112. https://doi.org/10.1016/S0165-232X(97)00011-6
  6. Ferziger, J.H., and Peric, M. (2002). Computational methods for fluid dynamics, Springer, London, UK.
  7. Fujita, I., and Tsubaki, R. (2003). "Convection velocity measurement of river surface ripples by using space-time images." Advances in River Engineering, Vol. 9, pp. 55-60. (in Japanese)
  8. Fujita, I., Watanabe, H., and Tsubaki, R. (2005). "Efficient analysis method for river flow measurement using space-time images." IAHR Conference, pp. 422-428.
  9. Ghia, U., Ghia, K.N., and Shin, C.T. (1982). "High-resolutions for incompressible flow using the Navier-Stokes equations and a multigrid method." Journal of Computational Physics, Vol. 48, pp. 387-411. https://doi.org/10.1016/0021-9991(82)90058-4
  10. Jahne, B. (1993). Spatio-temporal image processing. Springer, Berlin, Germany.
  11. Kim, S.J., Yu, K., and Yoon, B.M. (2011). "Real-time discharge measurement of the river using fixed-type surface image velocimetry." Journal of Korea Water Resources Association, Vol. 44, No. 5, pp. 377-388. (in Korean) https://doi.org/10.3741/JKWRA.2011.44.5.377
  12. Kim, Y., Won, N.I., Noh, J., and Park, W.C. (2015) "Development of high-performance microwave water surface current meter for general use to extend the applicable velocity range of microwave water surface current meter on river discharge measurement." Journal of Korea Water Resources Association, Vol. 48, No. 8, pp. 613-623. (in Korean) https://doi.org/10.3741/JKWRA.2015.48.8.613
  13. Miyaura, E., Nakajima, Y., and Yoshimura, A. (2012). "Fixed microwave current meter and RYUKAN, facing pratical and fullfledged use." New Era of River Water Discharge Water Measurement, Vol. 3, pp.55-60 (in Japanese)
  14. Notoya, Y., Fujita, I., and Tateguchi, S. (2017). "Development of river surface velocity vectors by using three dimensional space-time volume of surface images." Journal of Japan Society of Civil Engineers, B1 (Water Engineering), Vol. 73, No. 4, pp. I_511-I_516. (in Japanese)
  15. Raffel, M., Willert, C.E., Scarano, F., Kahler, C.J., Wereley, S.T., and Kompenhans, J. (2018). Particle image velocimetry, a practical guide. 3rd ed, Springer, Berlin, Germany.
  16. The Visualization Society of Japan (VSJ) (2002). PIV Handbook, Morokita Publishing, Tokyo, Japan (in Japanese).
  17. Yamaguchi, T. (2011). "Introduction of several examples of curious H-Vs relationship including cases with wrong installation of radio current meters." New Era of River Water Discharge Water Measurement, Vol. 2, pp. 20-27 (in Japanese)
  18. Yu, K., Kim, S., and Kim, D. (2014). "Measurement of two-dimensional velocity distribution of spatio-temporal image velocimeter using cross-correlation analysis." Journal of Korea Water Resources Association, Vol. 47, No. 6, pp. 537-546. (in Korean) https://doi.org/10.3741/JKWRA.2014.47.6.537
  19. Yu, K., Kim, S., and Kim, D. (2015). "Correlation analysis of spatiotemporal images for estimating two-dimensional flow velocity field in a rotating flow condition." Journal of Hydrology, Vol. 529, pp. 1810-1822. https://doi.org/10.1016/j.jhydrol.2015.08.005
  20. Yu, K., and Park, M.H. (2016). Particle image velocimetry, CIR. (in Korean)
  21. Yu, K., and Whang, J.G. (2016). "Development of real-time surface image velocimeter using an android smartphone." Journal of Korea Water Resources Association, Vol. 49, No. 6, pp. 469-480. (in Korean) https://doi.org/10.3741/JKWRA.2016.49.6.469
  22. Yu, K., and Whang, J.G. (2017). "Measurement of surface velicity in open channels using cameras on a drone." Journal of Disaster Management, Vol. 17, No. 2, pp. 403-413. (in Korean)
  23. Zhang, Z., Wang, H., Yan, X., Gao, H., and Li, C. (2017) "Sensitivity analysis and uncertainty evaluation of space-time image velocimetry." Chinese Journal of Scientific Instrument, Vol. 38, No. 7, pp. 1763-1771. (in Chinese)