• Journal of Biomedical Engineering Research
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• v.21 no.2
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• pp.129-136
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• 2000

중재적 시술을 위한 자기공명영상(MRI)용 주자석은 수직 자계를 가지는 경우가 대부분인데 본 논문에서는 수직 자계를 발생하는 주자석에 장착할 수 있는 볼록형 경사자계코일을 소개하였다. 중재적 시술에 필요한 고속 촬영을 하기 위해서는 강한 경사자계 및 낮은 코일 인덕턱스가 필요한데 본 논문에서는 이를 효율적으로 실현하기 위해 경사자계코일을 볼록 곡면 위에 실현하였다. 기존 방법에서처럼 평면 위에 경사자계코일을 실현하지 않고 볼록 곡면 위에 실현함으로써 경사자계코일의 자계 강도 특성 및 코일 인덕턱스 특성을 향상시킬 수 있을 뿐만 아니라 중재적 시술을 위한 경사자계코일 내 공간을 충분히 확보할 수 있다. Prolate spheroid 좌표계에서 표현되는 경사자계코일 면을 정의하였고, 유한요소법을 이용한 볼록형 경사자계코일 설계 방법을 기술하였다. 또한 경사자계코일 면의 곡률에 따라 경사자계코일의 성능이 어떻게 변화하는지에 대한 결과를 제시하였다.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.76-83
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• 2007

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.2
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• pp.259-266
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• 2010

The heat flowrate and pressure dorp of $CO_2$ in a multi-tube-in-tube helical coil type gas cooler were predicted using LMTD method and compared with the experimental data. The mass flowrate of $CO_2$ and coolant were varied from 0.06 to 0.075 [kg/s], and the cooling pressure of gas cooler were from 8 to 10 [MPa], respectively. The LMTD method is used to predict the heat flowrate and pressure drop of supercritical $CO_2$ during in-tube cooling. The equations used by LMTD method were Gnielinski correlation for $CO_2$ and Dittus-Boelter correlation for coolant, respectively. The equation used to predict the pressure drop of $CO_2$ and coolant is Blasius correlation. In comparison of heat flowrate and pressure drop of $CO_2$ measured by experiment to that predicted by LMTD method, the experimental heat flowrate and pressure drop of $CO_2$ in the multi-tube-in-tube helical coil type gas cooler shows a relatively good agreement with that predicted by LMTD method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.657-665
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• 2019

In this study, we conducted a study on the transcranial magnetic electrode, a method for the study of dementia and muscle pain, a neurodegenerative disease caused by an aging society, which is becoming a problem worldwide. In particular, transcranial magnetic electrodes have been studied to improve their ability to be deteriorated by dementia symptoms such as speech, cognitive ability, and memory by outputting magnetism deep into the brain using coils on the head epidermis. In this study, simulation was performed using Maxwell 3D program for the design of coil, the core of transcranial magnetic electrode. As a result of the simulation comparison between the coil designed by the previous research and the coil through the research and development, the output was found to be superior to the conventional designed coil. The graphs of the coil outputs of B-Field and H-Field are found to be symmetrical, but the symmetry between each coil is pseudo-symmetrical and not accurate. Based on these results, an experiment was conducted to confirm whether the output of the head epidermis through both coils is possible. In the magnitude field of the reverse-coil 2-coil analysis, the maximum output was 3.3920e + 004 H [A_per_meter], and the vector field showed the strongest magnetic field around 35 to 165 degrees. It was confirmed that the magnetic output canceled due to the magnetic output. In the case of the forward 2-coil, a maximum of 3.2348e + 004H [A_per_meter] similar to the reverse coil was observed, but in the case of the vector field, the magnetic output regarding the forward output and the head skin output was confirmed. However, when the height change in the output coil, the magnetic output was reduced.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.6 s.261
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• pp.651-658
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• 2007

A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.844-847
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• 2002

본 논문에서는 단상 thyristor 정류기 구조의 대전력 150KVA급의 mash seam 용접기에 용접 센터링등 여러 가지 용접 효율 향상을 위한 부가 장치를 포함한 용접장치 개발을 통한 용접품질 분석결과를 보이고 있다. 일반적으로 제철소에 사용되는 수10KVA급의 용접기들은 그동안 전량 수입에 의존하던 것을 공동연구를 통해서 국산화에 성공하였다. 본 시스템은 기존의 타사제품의 기능을 포함하여 용접 센터링 장치, 용접 전후단 의 크램핑기능, 선후행 코일의 선단부를 절단하는 shear ing 기능, 용접 휠높이 자동조절기능을 포함하였으며, 자체 설계된 대전력용 변압기, 대전력 절환용 thyristor 제어들을 포함한 용접기로써 기존의 타사제품에 비하여 기능적, 성능적으로 향상된 형태로써 용접 성능 검사에서도 양호한 결과 얻었다. 본 논문에서는 mash seam 용접기의 기본적인 기능설명과 개된 용접기를 기능별로 설명하고, 실용접 결과를 소개하여 향후 계획을 제시한다

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.61-62
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• 2006

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.771-773
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• 2003

본 논문에서는 대전력 150KVA급의 mash seam 용접기에 용접 센터링등 여러 가지 용접 효율 향상을 위한 부가 장치를 포함한 용접장치 개발을 통한 용접품질 분석결과를 보이고 있다. 일반적으로 제철소에 사용되는 수100KVA급의 용접기들은 그동안 전량 수입에 의존하던 것을 공동연구론 통해서 국산화에 성공하였다. 본 시스템은 기존의 타사제품의 기능을 포함하여 용접 센터링 장치, 용접 전후단의 크램핑기능, 선후행 코일의 선단부를 절단하는 shearing 기능, 용접 휠높이 자동조절기능을 포함하였으며, 자체 설계된 대전력용 변압기, 대전력 절환용 thyristor 제어들을 포함한 용접기로써 기존의 타사제품에 비하여 기능적, 성능적으로 향상된 형태로써 용접성능 검사에서도 양호한 결과 얻었다. 본 논문에서는 mash seam 용접기의 기본적인 기능설명과 개발된 용접기를 기능별로 설명하고, POSCO 현장적용 결과를 간략히 소개한다.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.8 s.185
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• pp.80-88
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• 2006

This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED illuminator and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of hot rolled steel strip are used to develop KNN (k- Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.379-383
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• 2005

This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED light and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of cold roll steel strips are used to develop KNN (k-Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.