• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.270-279
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• 2003

Parametric studies have been conducted into the variability of the factors affecting the ultrasonic testing applied to weldments. The influence of ultrasonic equipment, transducer parameters, test technique, job parameters, defect type and characteristics on reliability far defect detection and sizing was investigated by experimentation. The investigation was able to build up substantial bank of information on the reliability of manual ultrasonic method for testing weldments. The major findings of the study separate into two parts, one dealing with correlation between ultrasonic techniques, equipment and defect parameters and inspection performance effectiveness and other with human factors. Defect detection abilities are dependent on the training, experience and proficiency of the UT operators, the equipment used, the effectiveness of procedures and techniques.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.136-146
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• 2022

Some surface defects make the weak quality of steel materials. To limit these defects, we advocate a one-stage detector model RetinaNet among diverse detection algorithms in deep learning. There are several backbones in the RetinaNet model. We acknowledged two backbones, which are ResNet50 and VGG19. To validate our model, we compared and analyzed several traditional models, one-stage models like YOLO and SSD models and two-stage models like Faster-RCNN, EDDN, and Xception models, with simulations based on steel individual classes. We also performed the correlation of the time factor between one-stage and two-stage models. Comparative analysis shows that the proposed model achieves excellent results on the dataset of the Northeastern University surface defect detection dataset. We would like to work on different backbones to check the efficiency of the model for real world, increasing the datasets through augmentation and focus on improving our limitation.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.63-68
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• 2022

In this study, we produced defect detection models using parallel convolution neural networks. If convolution neural networks are constructed parallel type, the model's detection accuracy will increase and detection time will decrease. We produced parallel-type defect detection models using 4 types of convolutional algorithms. The performance of models was evaluated using evaluation indicators. The model's performance is detection accuracy and detection time. We compared the performance of each parallel model. The detection accuracy of the model using AlexNet is 97 % and the detection time is 0.3 seconds. We confirmed that when AlexNet algorithm is constructed parallel type, the model has the highest performance.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.55-61
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• 2021

In this paper, we proposed and implemented defect detection methods of polarized film with half-wave phase retardation plates. We investigated the principles of phase retardation compensation and optical principle of half-wave phase retardation plates. We analyzed of samples of polarized film with half-wave phase retardation plates. The optical defect detection methods are proposed and the performance is validated with experiments.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.37-44
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• 2001

Ultrasonic testing has a characteristics such as excellent permeability, high-sensitivity to find defect and an almost exact measurement for position. size and direction of inner defect, which differ from other non-destructive testing. In the study, we developed program into optimal testing condition, to distinguish obstacle echo and defect position. This program shows generation and processing of ultrasonic pulse. We compared simulation with ultrasonic test in 45$^\circ$, 60$^\circ$and 70$^\circ$transducer. Test results were in accordance with simulation within 0.1~7.2%.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.81-86
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• 2023

Recently, there has been an increased demand for light-emitting diode (LED) due to the growing emphasis on environmental protection. However, the use of GaN-based sapphire in LED manufacturing leads to the generation of defects, such as dislocations caused by lattice mismatch, which ultimately reduces the luminous efficiency of LEDs. Moreover, most inspections for LED semiconductors focus on evaluating the luminous efficiency after packaging. To address these challenges, this paper aims to detect defects at the wafer stage, which could potentially improve the manufacturing process and reduce costs. To achieve this, image processing and deep learning-based defect detection techniques for Sapphire Epi-Wafer used in Green LED manufacturing were developed and compared. Through performance evaluation of each algorithm, it was found that the deep learning approach outperformed the image processing approach in terms of detection accuracy and efficiency.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.504-508
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• 2022

Single crystal gallium oxide (Ga₂O₃) has been an emerging material for power semiconductor applications. However, the defect distribution of Ga₂O₃ substrates needs to be carefully characterized to improve crystal quality during crystal growth. We analyzed the type and the distribution of defects on commercial (-201) Ga₂O₃ substrates to get a basic standard prior to growing Ga₂O₃ crystals. Etch pit technique was employed to expose the type of defects on the Ga₂O₃ substrates. Synchrotron white beam X-ray topography was also utilized to observe the defect distribution by a nondestructive manner. We expect that the observation of defect distribution with three-dimensional geometry will also be useful for other crystal planes of Ga₂O₃ single crystals.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.567-576
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• 2020

This study proposes additional items to be recognized as defects in a defect lawsuit through a case analysis of lawsuit cases in apartment housing. Identifying these defects prevents an unexpected increase in litigation costs, delays in the date of litigation, and emotion repercussions or additional lawsuits. In this study, the defects that were not discovered by the existing occupants and construction companies, but were newly discovered in litigation, were defined as defects in lawsuits. Fifteen cases of lawsuits were analyzed and a total of 77 defects were derived. Each item was then reviewed for location, work type, number of occurrences, and cost. The results were yielded 23 defect items, which were validated by appraisers who directly appraised the cases. In addition, the derived defect factors were analyzed. Finally, the 23 defect items were categorized into 10 main factors which include attributes such as causes of occurrence and characteristics. This can provide an overall area of defects to be considered in addition to existing defect items in the life cycle of the housing. The results of this study can contribute to reducing the actual occurrence of defects and minimizing the disputes in the case of defect lawsuits.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1070-1077
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• 2011

This study intends to assess the defect in the weld zone of titanium grade 2 plate in terms of acoustical anisotropy based on the angle beam method. Depending on the rolling direction, the ratio of wave velocity was found to be 1.08 and the difference in the angle of refraction was more than seven degrees, confirming the presence of acoustical anisotropy. Thus for measuring the length of defect in the weld zone of the titanium plate (thickness of 10mm), the distance amplitude characteristics curves of titanium, TDACC-R and TDACC-T were constructed for the measurements in consideration of the acoustical anisotropy on CRT of the ultrasonic testing equipment. As a result, when the distance amplitude characteristics curve corresponds to the rolling direction, the length of defect was close to the actual measurement within 1mm and when different, the difference was found to be over 4mm. It was affirmed that the acoustical anisotropy should be taken into consideration when measuring the length of defects in the weld zone of the titanium plate with the presence of acoustical anisotropy.