• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.4
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• pp.611-621
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• 2001

This paper presents a design methodology of bandpass filter by using defect modes in photonic bandgap (PBG) structures. PBG structures are realized with alternating section of microstrip line arranged in a periodical manner. A passband is created within the stopband of PBG structures with defect modes, which can be generated by changing the period of certain part of PBG structure. We also extract a simple equivalent circuit of a bandstop filter by using several LC sections.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.23-29
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• 2015

In this paper, we suggest a method of detecting defects by applying Hough transform and least squares on ceramic images obtained from non-destructive testing. In the ceramic images obtained from non-destructive testing, the background area, where the defect does not exist, commonly show gradual change of luminosity in vertical direction. In order to extract the background area which is going to be used in the detection of defects, Hough transform is performed to rotate the ceramic image in a way that the direction of overall luminosity change lies in the vertical direction as much as possible. Least squares are then applied on the rotated image to approximate the contrast value of the background area. The extracted background area is used for extracting defects from the ceramic images. In this paper we applied this method on ceramic images acquired from non-destructive testing. It was confirmed that extracted background area could be effectively applied for searching the section where the defect exists and detecting the defect.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.53-55
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• 2005

The signals of the eddy current testing(ECT) for the examination of the steam generator(SG) tubes in the nuclear power plant(NPP) determine the existence, size, and kind of defects using the variation of impedance signals when a testing coil, driven by alternating current, passes through the SG tube contains defects. The aim of this paper is building a database of the RPC probe signals on the basis of the sizes variation of defects and frequency variation of probe. In this paper 3-D numerical analysis of the ECT signals using the finite element method is performed. Through this study, it is shown variation of magnitude and phase of impedance according to variation of defect size and frequency. From the result of this paper, we can obtain the information which is useful in defect discrimination of SG tube in nuclear power plant.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.63-68
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• 2004

The high pressure vessels that are constructed by welding process have many welding lines and most of the leakage defects are occurred on these welding lines. The acoustic emission(AE) technique has adopted to detect the defect location and leakage on welding parts, but the AE signal in leakage are incomplete due to the attenuation, reiteration, instability and limit of defect size. To overcome these troubles, the experiments in this study are conducted to measure the indirect media-propagated AE signal perpendicular to the leakage hole. The AE signals that are acquired from the direct and indirect media are analyzed, and the reliability of the indirect media-propagated AE signal are examined experimentally. By AE signal investigation, this method can be adopted to detect efficiently the leakage in welding parts.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.564-568
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• 2005

As functional requirements of automatic office machines like printers, ATMs, copying machines are on a trend for the higher speed and precision, extensive technical advances are being developed and implemented in the industry. Media transport system is a device to convey a sheet of paper in ATMs and printers. The stability of media transport system is a matter of concern as their operating throughput rapidly increases. And defects of belts or rollers in a transport system directly affect the level of stability of the system. Therefore an automatic diagnostic system for predicting various defects is necessary for the stable operation of the media transport system. A simulation based on multi-body dynamics has been done for a feasibility study of a system design for the defect anticipation.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.68-73
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• 2021

In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.59-64
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• 2020

In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.54-58
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• 2023

In this study, we compared the detection accuracy of the parameters of the scaffold failure detection model. A detection algorithm based on convolutional neural network was used to construct a failure detection model for scaffold. The parameter properties of the model were changed and the results were quantitatively verified. The detection accuracy of the model for each parameter was compared and the parameter with the highest accuracy was identified. We found that the activation function has a significant impact on the detection accuracy, which is 98% for softmax.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.247-248
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• 2007