• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.899-904
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• 2011

Inspections and diagnoses of corona discharge are important in order to prevent electrical faults of external insulation in power systems. This paper studies a measurement of ultra-violet rays(UV) strength of corona discharges on insulators using a UV sensor with an optic lens. The data has been compared with the images of a UV camera. The UV sensor estimated that DC voltage needed to be set at 700V for accurate data analysis of the properties of UV detected during corona discharge. UV was generated at 60kV when the corona discharge occurred. UV strength and images of UV increased at a high voltage. The image area of the UV using a UV camera and the detection of UV using a UV sensor have shown, that the polymer insulator mounted on a live part must be checked when the applied voltage on the good polymer insulator is greater than 37.5% of its breakdown voltage.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.313-314
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• 2009

In this paper, it's described the UV detected images on polymer insulators using UV camera. The patterns of UV detected images are classified into 3 types such as jellyfish(J), amoeba(A), sunflower(S). J type is detected by high electric field in air A type is detected by early surface discharge. And, S type is detected by the serious problem in surface of insulator.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.81.3-81.3
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• 2019

In this study, we apply conditional Generative Adversarial Network, which is one of the deep learning method, to the image-to-image translation from solar magentograms to solar UV and EUV images. For this, we train a model using pairs of SDO/AIA 9 wavelength UV and EUV images and their corresponding SDO/HMI line-of-sight magnetograms from 2011 to 2017 except August and September each year. We evaluate the model by comparing pairs of SDO/AIA images and corresponding generated ones in August and September. Our results from this study are as follows. First, we successfully generate SDO/AIA like solar UV and EUV images from SDO/HMI magnetograms. Second, our model has pixel-to-pixel correlation coefficients (CC) higher than 0.8 except 171. Third, our model slightly underestimates the pixel values in the view of Relative Error (RE), but the values are quite small. Fourth, considering CC and RE together, 1600 and 1700 photospheric UV line images, which have quite similar structures to the corresponding magnetogram, have the best results compared to other lines. This methodology can be applicable to many scientific fields that use several different filter images.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.42.3-42.3
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• 2019

We translate Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA) ultraviolet (UV) multi-channel images into another UV single-channel image using a deep learning algorithm based on conditional generative adversarial networks (cGANs). The base input channel, which has the highest correlation coefficient (CC) between UV channels of AIA, is 193 Å. To complement this channel, we choose two channels, 1600 and 304 Å, which represent upper photosphere and chromosphere, respectively. Input channels for three models are single (193 Å), dual (193+1600 Å), and triple (193+1600+304 Å), respectively. Quantitative comparisons are made for test data sets. Main results from this study are as follows. First, the single model successfully produce other coronal channel images but less successful for chromospheric channel (304 Å) and much less successful for two photospheric channels (1600 and 1700 Å). Second, the dual model shows a noticeable improvement of the CC between the model outputs and Ground truths for 1700 Å. Third, the triple model can generate all other channel images with relatively high CCs larger than 0.89. Our results show a possibility that if three channels from photosphere, chromosphere, and corona are selected, other multi-channel images could be generated by deep learning. We expect that this investigation will be a complementary tool to choose a few UV channels for future solar small and/or deep space missions.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.73.1-73.1
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• 2011

An understanding of the ultraviolet (UV) properties of nearby galaxies is essential for interpreting images of high redshift systems. In this respect, the prediction of optical-band morphologies at high redshifts requires UV images of local galaxies with various morphologies. We present the simulated optical images of galaxies at high redshifts using diverse and high-quality UV images of nearby galaxies obtained through the Galaxy Evolution Explorer (GALEX). We measured CAS (concentration, asymmetry, clumpiness) as well as Gini/M20 parameters of galaxies at near-ultraviolet (NUV) and simulated optical images to quantify effects of redshift on the appearance of distant stellar systems. We also discuss the change of morphological parameters with redshift.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04a
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• pp.47-48
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• 2008

본 연구는 제작된 OLED 소자에 UV의 조사시간에 따른 PL intensity 의 감소와 UV power에 따른 PL degradation 변화에 따라 적절한 UV의 조사조건을 찾아 OLEO 소자의 사진이미지를 구현하고자 하였다. 이러한 조건들로부터 얻어진 OLED 소자의 사진이미지 구현을 통하여 그동안 문제점으로만 여겨졌던 UV에 의한 PL degradation 현상이 문제점만이 아닌 다른 하나의 장점으로 발전되어 다른 분야에서 적용될 수 있다고 기대해본다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1590-1591
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• 2011

In this paper, the UV corona camera was developed using the solar blind and Multi Channel Plate(MCP) technology for the target localization of UV camera. UV camera developed a $6.4^{\circ}{\times}4.8^{\circ}$ of the field of view as a conventional camera to diagnose a wide range of slightly enlarged, and power equipment to measure the distance between the camera and the distance meter has been attached. The UV camera was developed and measured using a UV image, as applied voltage increased ultraviolet images of the phenomenon could be obtained. And we investigated properties of UV corona image on insulator in salt water environments. From the results, the breakdown voltage was decreased and UV images were taken at low voltages and the UV image is rapidly increased with increasing High voltage.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.215-218
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• 2009

In this paper, there analyzed the UV behavior and detection images due to corona discharge of insulators at 22.9kV. As the results, the shapes of UV detection images are jellyfish, sunflower, and amoeba type. Generally, the jellyfish and sunflower type appeared in air discharge. In surface discharge, Amoeba is generated. Also, there are classified 8 patterns such as sunflower A or B, jellyfish A or B, amoeba A, B, C, D. This method of the facilities assessment has an immediate effect in the field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3540-3545
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• 2009

Due to recent development of high temperature high pressure(HTHP) diamond synthetic and treatment technology, we need to identify the natural diamonds fast, reliable, and economically. We proposed using new method of UV fluorescence and X-ray Lang topography imaging for distinguishing one synthetic diamond from four natural colored diamonds. We observe unique local stress field uneven image in synthetic diamond using UV fluorescence and Lang topography characterization, while uniform images in natural diamonds. Especially, X-ray Lang method offered the better identification power with better high resolution on stress field images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.167-174
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• 2010

In this paper, the ultraviolet rays images and aging judgement caused by surface contamination on 22.9[kV] class insulators was defined. UV images represented by the corona discharge are divided 3 types such as sunflower, jellyfish, amoeba and in detail, there are classified the progress mechanism of eight. In the field which is installed the power facilities, immediately, this judgement method can be found out the deteriorated parts of the power facilities. These steps are possible to judge the deterioration of power facilities through reliable data. Hereafter, this study as the diagnostic technology suitable for the sites is used.