• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.3
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• pp.398-407
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• 1999

In the present image processing technique, the concept of the gradient indicator(GI) has been introduced to find out the depth-of-field in sizing large particles ranging from $30{\mu}m$ to $30{\mu}m$ where using of the concept of the normalized contrast value(VC) is not appropriate. The gradient indicator is defined as the ratio of the local value to the maximum possible value of the gray-level gradient in an image frame. The gradient indicator decreases with the increases of the particle size and the distance from the exact focal plane. A particle is considered to be in focus when the value of the gradient indicator at its image boundary stays above a critical value. This critical gradient indicator($GI_{critical}$) is defined as the maximum gradient indicator($GI_{max}$) subtracted by a constant ${\Delta}GI$ which is to account for the particle-size effect. In the present ca.so, the value of ${\Delta}GI$ was set to 0.28 to keep the standard deviation of the measured particles mostly within 0.1. It was also confirmed that, to find the depth-of-field for small particles(${\leq}30{\mu}m$) with the same measurement accuracy, tho concept of the critical normalized contrast($VC_{critical}$) is applicable with 85% of the maximum normalized contrast value($VC_{max}$). Finally, the depth-of-field was checked for the size range between $10{\mu}m$ and $300{\mu}m$ when the both in-focus criteria ($GI_{critical}$ and $VC_{critical}$) were adopted. The change of the depth-of-field with the particle size shows good linearity in both the VC-applicable and the GI-applicable ranges with a reasonable accuracy.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.10a
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• pp.115-123
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• 1998

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under different experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are shape fractal dimension and surface fractal dimension. The shape fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Tribology and Lubricants
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• v.18 no.2
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• pp.147-152
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• 2002

The morphological analysis of wear particle is a very effective means fur machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing. These descriptors to analyze shape and surface of wear particle are shape fractal dimension and surface fractal dimension. The boundary fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal parameter.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.06a
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• pp.30-35
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• 2001

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried oui under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are share fractal dimension and surface fractal dimension. The boundry fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined b)r sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.53-58
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• 2001

Fractal dimension is the method to measure the roughness and the irregularity of something that cannot be defined obviously by Euclidean dimension. And the analysis method of this dimension don't need perfect, accurate boundary and color like analysis lot diameter, perimeter, aspect or reflectivity of wear particles or surface. If we arranged the morphological characteristic of various wear particle by using the characteristic of fractal dimension, it might be very efficient to the diagnosis of driving condition. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are boundary fractal dimension and surface fractal dimension.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.211-221
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• 1998

A digital image processing technique which is able to get the velocity vector distribution of a surface of the spilled oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.291-302
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• 1998

A digital image processing technique which is able to be used for getting the velocity vector distribution of a surface of the spilt oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.7
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• pp.53-65
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• 1995

입자화상 처리기법은 유체역학 분야의 정량적 유동가시화에 있어서 중요한 역할을 하고 있다. 회전 유동의 측면 사진을 찍을 때, 측정부의 볼록면 때문에 그 영상에서 광학적 변형이 일어나게 된다. 이러한 변형은 측정부의 형상은 물론 회전유동의 방향에 의해서도 큰 영향을 받는다. 정확한 유동장을 얻기 위해서 이러한 변형이 적절한 방법에 의하여 교정된다. 교정한 실험 데이터를 수치해석 결과와 비교해 보면 정량적으로 잘 맞는 것을 알 수 있다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.11
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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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.4
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• pp.504-511
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• 2000

PIV(Particle Image Velocimetry) is a recently developed technique for visualizing the fluid velocity fields. Because it has several advantages over the LDV(Laser Doppler Velocimetry), it became one of the most popular diagnostic tools in spite of its short history. However, its application to combustion is restricted by some problems such as flame illumination, scattered light refraction, particle density variation due to heat release, the combined effect of abrupt change in particle density and fluid velocity on flame contour, and thermophoresis which is particle lagging due to temperature gradient. These problems are expected to be originated from the non-continuous characteristics of flames and the limitations of particle dynamics. In the present study, these problems were considered for the visualization of the instantaneous coaxial hydrogen diffusion flame. And the instantaneous flame contour was detected using particle density difference. The visualized diffusion flame velocity field shows its turbulent and meandering nature. It was also observed that the flame is located inside the outer shear layer and flame geometry is largely influenced by the vorticity.