• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.05b
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• pp.291-293
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• 2000

In 64M DRAM, sub-1/4m NMOSFETs with STI(Shallow Trench Isolation), anomalous hump phenomenon of subthreshold region, due to capped p-TEOS/SiN interlayer induced defect, is reported. The hump effect was significantly observed as channel length is reduced, which is completely different from previous reports. Channel Boron dopant redistribution due to the defect should be considered to improve hump characteristics besides consideration of STI comer shape and recess.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.169-176
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• 2001

Defect of apple was depreciated the product value and causes storage disease seriously. To detect the defect of ‘Fuji’apple with machine vision system, the optical characteristics of defect should be investigated. In this research, absorbance spectra of defect were acquired by spectrophotometer in the range of visible and NIR region(400∼1,100nm) and L*a*b* color values were also acquired by colorimeter. NIR machine vision system was constructed with B&W camera, frame grabber, 16 tungsten-halogen lamps, variable focal length lens and NIR bandpass filter which was mounted to lens outward. Average gray values of defect at 15 NIR wavelength were acquired and the significant NIR wavelength was selected by comparing Mahalanobis distance between sound and defective apple. As the result of Mahalanobis distance analysis, the significant wavelength to discriminate the defectives in ‘Fuji’apple were found to be 720nm for scab and 970nm for bruise and cuts and 920nm was also effective regardless of defective types.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.10
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• pp.451-457
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• 2003

The silicon wafer is stable status at room temperature, but it is weak at high temperatures which is necessary for it to be fabricated into a power semiconductor device. During thermal diffusion processing, a high temperature produces a variety thermal stress to the wafer, resulting in device failure mode which can cause unwanted oxide charge or some defect. This disrupts the silicon crystal structure and permanently degrades the electrical and physical characteristics of the wafer. In this paper, the electrical characteristics of a single oxide layer due to high temperature diffusion process, wafer resistivity and thickness of polyback was researched. The oxide quality was examined through capacitance-voltage characteristics, defect density and BMD(Bulk Micro Defect) density. It will describe the capacitance-voltage characteristics of the single oxide layer by semiconductor process and device simulation.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.64-69
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• 2021

In this paper, a method for improving the defect classification performance in low contrast, ununiformity and featureless steel plate surfaces has been studied based on deep convolution neural network and transfer-learning neural network. The steel plate surface images have low contrast, ununiformity, and featureless, so that the contrast between defect and defect-free regions are not discriminated. These characteristics make it difficult to extract the feature of the surface defect image. A classifier based on a deep convolution neural network is constructed to extract features automatically for effective classification of images with these characteristics. As results of the experiment, AlexNet-based transfer-learning classifier showed excellent classification performance of 99.43% with less than 160 seconds of training time. The proposed classification system showed excellent classification performance for low contrast, ununiformity, and featureless surface images.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.1-6
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• 2020

In this paper, a method for improving the defect classification performance in steel plate surface has been studied, based on DWT(discrete wavelet transform) and SVM(support vector machine). Surface images of the steel plate have low contrast, uneven, and featureless, so that the contrast between defect and defect-free regions is not discriminated. These characteristics make it difficult to extract the feature of the surface defect image. In order to improve the characteristics of these images, a synthetic images based on discrete wavelet transform are modeled. Using the synthetic images, edge-based features are extracted and also geometrical features are computed. SVM was configured in order to classify defect images using extracted features. As results of the experiment, the support vector machine based classifier showed good classification performance of 94.3%. The proposed classifier is expected to contribute to the key element of inspection process in smart factory.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1360-1364
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• 2014

In this paper, RCS characteristics on defect pattern of crossed dipole slot FSS having a finite size have been analyzed. To analyze RCS, we applied the electric field integral equation analysis which applies BiCGSTab algorithm with iterative method and uses RWG basis function. To verify the validity of this paper, RCS of PEC sphere has been compared to the theoretical results and FSSs with defect patterns are fabricated and measured. As defect patterns in FSS, missing one column, missing some elements, and discontinuity in surfaces are simulated and compared with the measurement results. Resonant frequency shifts in pass band and changes in bandwidth are observed. From the results, precisely predicting and designing frequency characteristics over defect patterns are essential when applying FSS structures such as FSS radomes.

• Geomechanics and Engineering
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• v.22 no.5
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• pp.461-473
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• 2020

Natural rock mass contains defects of different shapes, usually filled with inclusions such as clay or gravel. The presence of inclusions affects the failure characteristics and mechanical properties of rock mass. In this study, the strength and failure characteristics of rock with inclusions were studied using the particle flow code under uniaxial compression. The results show that the presence of inclusions not only improves the mechanical properties of rock with defects but also increases the bearing capacity of rock. Circular inclusion has the most obvious effect on improving model strength. The inclusions affect the stress distribution, development of initial crack, change in crack propagation characteristics, and failure mode of rock. In defect models, concentration area of the maximum tensile stress is generated at the top and bottom of defect, and the maximum compressive stress is distributed on the left and right sides of defect. In filled models, the tensile stress and compressive stress are uniformly distributed. Failing mode of defect models is mainly tensile failure, while that of filled models is mainly shear failure.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.633-641
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• 2016

Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2000-2004
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• 2009

In general, for the condition monitoring of a power transformer using the UHF PD measuring technique, detection of any partial discharge, identifying the defect in the transformer and locating the insulation defect are necessary. In this paper one of the most frequent detects which can result in turn to turn fault in power transformer was examined for identifying the defect. In order to model the defect, as a discharge source, a partial discharge cell was used for experimental activity. Magnitude of electromagnetic wave signals and corresponding amount of apparent discharge were measured simultaneously against phase of applied voltage to the discharge cell. Frequency range and phase resolved partial discharge signals were measured and analyzed. The results will be contributed to build the defect database of power transformer and to decrease the occurrence of transformer faults.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.819-821
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• 2001

This paper describes a characteristics of MFL according to the position of Hall sensor Magnetic Flux Leakage(MFL) Method is used to detect surface defect in ferromagnetic plate. A plate has a surface defect and magnetizing equipment are producted to perform Non-Destructive Testing(NDT) using MFL. The SM 45C carbon steel plate is adopted to this experiment. there is a artifical defect with a twice of thickness and a half of depth of plate. Magnetizing equipment is composed of yoke made by layer-built of silicon sheet steel, NdFeB magnetic and iron brushes. Detecting defect is performed by MFL NDT using Hall sensor. It is shown that magnetic flux detected by Hall sensor is affected according to the position of Hall sensor through MFL experiment and numerical analysis.