Author(s): Kwonkyu Yu; Namjoo Lee

Linked Author(s): Kwonkyu Yu, Namjoo Lee

Keywords: Spatio-temporal image; Spatio-temporal volume; Surface-image velocimetry; Autocorrelogram; Fast Fourier transform

Abstract: The surface image velocimetry was developed to measure river flow velocity safely and effectively in flood season. There are a couple of methods in surface image velocimetry. Among them a spatio-temporal image velocimetry is in the spotlight, since it can estimate mean velocity over a period of time. For the spatio-temporal image velocimetry analyzes a series of images all at once, it can reduce analysis time so much. It, however, has a severe drawback to find out the main flow direction. If the direction of spatio-temporal image does not coincide to the main flow direction, it can cause a big error in velocity. The present study aims to propose a new method to find out the main flow direction by using autocorrelogram and the fast Fourier transform 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 an autocorrelogram was made from the spatio-temporal volume along the time direction. We analyzed this autocorrelogram by using FFT and figured out the main flow direction from the transformed image. Then a spatio-temporal image was extracted in main flow direction 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.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022886

Year: 2022