• Journal of Ocean Engineering and Technology
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• 제10권3호
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• pp.89-95
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• 1996

The flow field around four cylinders for various angles was investigated utilizing particle image velocimetry(PIV) technique. Flow field was recorded by video camera first. Then application of PIV technique was done to the flow field. The results turned out to be useful to analyze complex flow field around multiple cylinders.

• Journal of Sensor Science and Technology
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• 제32권5호
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• pp.307-312
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• 2023

To measure the flow velocity and direction in the near field of an unmanned underwater vehicle, an optical measurement unit containing an image sensor and a phosphor-integrated pillar that mimics the neuromasts of a fish was constructed. To analyze pillar movement, which changes with fluid flow, fluorescence image analysis was conducted. To analyze the flow velocity, mean force analysis, which could determine the relationship between the light intensity of a fluorescence image and an external force, and length-force analysis, which could determine the distance between the center points of two fluorescence images, were employed. Additionally, angle analysis that can determine the angles at which pixels of a digital image change was selected to analyze the direction of fluid flow. The flow velocity analysis results showed a high correlation of 0.977 between the external force and the light intensity of the fluorescence image, and in the case of direction analysis, omnidirectional movement could be analyzed. Through this study, we confirmed the effectiveness of optical flow sensors equipped with phosphor-integrated pillars.

• Journal of Korea Water Resources Association
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• 제54권11호
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• pp.933-942
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• 2021

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.

• Transactions of the Korean Society of Mechanical Engineers B
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• 제24권2호
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• pp.153-160
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• 2000

A Particle Image Velocimetry(PIV) algorithm is developed to analyze whole flow field both qualitatively and quantitatively. The practical use of PIV requires the use of fast, reliable, computer-based methods for tracking numerous particles suspended in a flow field. The TSS, NTSS, FFT-Hybrid, which are developed in the area of image compression and coding, are introduced to develop fast vector search algorithm. The numerical solution of the lid-driven cavity flow by the ADI algorithm with the Wachspress Formula is introduced to produce synthetic data for the validation of the tracking algorithms. The algorithms are applied to image data of real flow experiments. The comparisons in CPU time and mean error show, with a small loss of accuracy, CPU time for tracking is reduced considerably.

• Convergence Security Journal
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• 제22권4호
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• pp.129-133
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• 2022

Deep learning frameworks are still evolving, and there are various frameworks. Typical deep learning frameworks include TensorFlow, PyTorch, and Keras. The Deepram framework utilizes optimization models in image classification through image learning. In this paper, we use the TensorFlow and PyTorch frameworks, which are most widely used in the deep learning image recognition field, to proceed with image learning, and compare and analyze the results derived in this process to know the optimized framework. was made.

• Transactions of the Korean Society of Mechanical Engineers B
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• 제27권11호
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• pp.1572-1578
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• 2003

Particle Image Thermometry(PIT) with liquid crystal tracers is used for visualizing and analysis of the bubbly flow in a vertical temperature gradient. Quantitative data of the temperature were obtained by applying the color-image processing to a visualized image, and neural-network was applied to the color-to-temperature calibration. This paper describes the method, and presents the transient mixing temperature patterns of the bubbly flow.

• Journal of information and communication convergence engineering
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• 제9권3호
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• pp.319-324
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• 2011

In computing the optical flow. Horn and Schunck's method which is a representative algorithm is based on differentiation. But it is difficult to estimate the velocity for a large displacement by this algorithm. To cope with this problem multigrid method has been proposed. In this paper, we have proposed a scaled multigrid algorithm which the initial flow for a level is calculated by the summation of the optimally scaled flow and error flow. The optimally scaled flow is the scaled expanded flow of the previous level, which can generate an estimated second image having the least RMS error with respect to the original second image, and the error flow is the flow between the estimated second image (generated by the optimally scaled flow) and the original second image. The flow for this level is then estimated using the original first and second images and the initial flow for that level. From among the various coarsest starting levels of the multigrid algorithm, we select the one that finally gives the best estimated flow. Better results were achieved using our proposed method compared with Horn and Schunck's method and a conventional multigrid algorithm.

• Journal of the Korea Society of Computer and Information
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• 제10권1호
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• pp.223-229
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• 2005

In this paper a coarse-to-fine optical flow detection method is proposed. Provided that optical flow gives reliable approximation to two-dimensional image motion, it can be used to recover the three-dimensional motion, but usually to set the reliable optical flows are difficult. The proposed algorithm uses Horn's algorithm for detecting initial optical flow, then Thin Plate Spline is introduced to warp a image frame of the initial optical flow to the next image frame. The optical flow for the warped image frame is again used iteratively until the mean square error between two image sequence frames is lowered. The proposed method is experimented for the real moving picture image sequence. The proposed algorithm gives dense optical flow vectors.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• 제7권3호
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• pp.8-14
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• 2011

The clogging of the flow area at the tube support plates(TSPs), especially at the upper TSPs results in the water level oscillation of a steam generator during normal operation. A reduction of the TSP flow area causes to increase in pressure drop within the two-phase flow zone, which destabilizes the boiling flow through the tube bundle. This phenomenon was occasionally observed at a few domestic and foreign nuclear power plants. One of the methods for defining the flow area clogging is visual inspection, which is the most effective inspection method. The results of the visual inspection for TSPs' flow area are clogging images on TSPs' quartrefoil lobes. These images are complexly distorted due to lens aberration and external factors like the distance to a subject and angle etc. In this work, we developed the analysis algorithm for clogging image of the TSP flow area of steam generators. For this purpose, we designed an image verification device applicable to the camera employed in the field for visual inspection and then, we demonstrated the validity of image analysis algorithm by using this device and commercial autoCAD program.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권2호
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• pp.1688-1691
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• 2007

This paper shows that the boundary image sticking can be prohibited completely by using the vacuum sealing process, which means that the residual impurities such as nitrogen or oxygen can be a critical factor inducing the boundary image sticking. The production of boundary image sticking was checked in the test panel fabricated by the $N_2$ or $O_2$ flow during the vacuum sealing process. As a result, the boundary image sticking did not appear in the case of $N_2flow$, whereas the boundary image sticking was observed in the case of $O_2$ flow even though the test panel was fabricated by the vacuum sealing process.