• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.334-343
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• 1996

Quality evaluation for food and agricultural products have always been one of the most elusive problems associated with the handling , processing and marketing in a food plant production. In order to detect physical foreign materials in food and agricultural products, non-destructive techniques have been developed for many years. Application of X-ray system to detect physical foreign materials in food and agricultural products could be considered to be a high potential method. Especially , it is impossible to detect internal physical foreign materials by visual inspections. In this study, it was tried to be applied for two different X-ray devices. Soft X-ray system with CdTe sensor and X-ray CT scanner were evaluated for advantage of the detection of non-meltallic foreign materials in food and agricultural products . Though the soft X-ray is not a high energy radiation, it is possible to detect small different density in a material. The CdTe sensor has a high resolution for t e soft X-ray energy region. The density characteristics of foods and foreign material were expressed region. The density characteristics of foods and foreign materials were expressed as a soft X-ray energy spectrum. The energy spectrum was analyzed by a personal computer with a multi-channel analyzer. X-ray CT scanner can provide visual image and analyze by three dimensional information inside food and agricultural products. The X-ray CT scanner using as a medical equipment was used to detect a foreign material. The density characteristics of food and foreign materials in food were tried to be detected by the threshold value on the basis of the CT numbers. The soft X-ray absorption characteristics for acrylin plates and distilled water were obtained and could be found the possibility of detecting a small physical foreign materials such as a plastic wrapping film , a stone and grasshopper in food and agricultural products.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.4
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• pp.295-299
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• 2016

Residual foreign objects at the secondary side (top of the tubesheet and tube support plates) of a steam generator are likely to cause a leak by causing wear in the tube. The extent of wear is significantly affected by the material, shape, and size of the foreign object, and the corrosion properties of the tube. The presence of foreign objects at the top of the tubesheet and tube support plates has been identified using remote visual inspection methods such as the foreign object search and retrieval and eddy current test (ECT). The detection of the residual foreign object at the secondary side of a steam generator has limitations that depend on the material properties and the condition of contact with the tube. In this study, which is vertical and horizontal from the upper tubesheet, the corresponding bobbin ECT signals were collected and analyzed to measure its ability to detect foreign objects.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.6
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• pp.398-406
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• 2015

This paper explored the results of experimental investigation on carbon fiber reinforced polymer (CFRP) composite sample with thermal wave technique. The thermal wave technique combines the advantages of both conventional thermal wave measurement and thermography using a commercial Infrared camera. The sample comprises the artificial inclusions of foreign material to simulate defects of different shape and size at different depths. Lock-in thermography is employed for the detection of defects. The temperature field of the front surface of sample was observed and analysed at several excitation frequencies ranging from 0.562 Hz down to 0.032 Hz. Four-point methodology was applied to extract the amplitude and phase of thermal wave's harmonic component. The phase images are analyzed to find qualitative and quantitative information about the defects.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.6 no.2
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• pp.20-27
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• 2010

In order to prevent the corrosion of component contacted primary water designed alloy 600 material in the nuclear power plant. But the primary water stress corrosion cracking(PWSCC) of alloy 600 and weld area occurs continuously due to the residual stress. The leakage accident resulted from PWSCC in the drain nozzle of the steam generator of domestic power plants. Heater sleeves of the pressurizer are welded with alloy 600 weld material and therefore exposed to the primary water environment. PWSCC occurred in heater sleeve material and weld area of many foreign power plants. The current issue of domestic nuclear power plants are consequently concentrated to PWSCC of similar material. In order to improve the detection and the sizing of the PWSCC in the welding sleeve of the pressurizer, the automatic UT system and multi-directions probe sets have been developed. The experimental studies have been performed using the mock-up block containing artificial reflectors(ID connected EDM notch) and semi-artificial cracks made from thermal fatigue. The automatic UT System is applied in the detection and the length sizing of the ID/OD on the tube and the J-groove weld area of the artificial reflectors and results of the detection and the sizing are compared respectively. Also, the developed automatic UT system is successfully accomplished to inspect the heater sleeve and the J-groove weld area on the pressurizer for the detection of PWSCC.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.452-454
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• 2021

Currently, the security control market is operating based on AI technology. The reason for using AI is to detect large amounts of logs and big data between security equipment, and to alleviate time and human problems. However, problems are still occurring in the application of AI. The security control market is responding to many problems other than the problems introduced in this paper, and this paper attempts to deal with five problems. We would like to consider problems that arise in applying AI technology to security control environments such as 'AI model selection', 'AI standardization problem', 'Big data accuracy', 'Security Control Big Data Accuracy and AI Reliability', 'responsibility material problem', and 'lack of AI validity.'

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.149-156
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• 2024

This paper implemented a drill bit foreign matter inspection system based on the YOLO V3 algorithm and evaluated its performance. The study trained the YOLO V3 model using 600 training data to distinguish between the normal and foreign matter states of the drill bit. The implemented inspection system accurately analyzed the state of the drill bit and effectively detected defects through automatic inspection. The performance evaluation was performed on drill bits used more than 2,000 times, and achieved a recognition rate of 98% for determining whether resharpening was possible. The goal of foreign matter removal in the cleaning process was evaluated as 99.6%, and the automatic inspection system could inspect more than 500 drill bits per hour, which was about 4.3 times faster than the existing manual inspection method and recorded a high accuracy of 99%. These results show that the automated inspection system can dramatically improve inspection speed and accuracy, and can contribute to quality improvement and cost reduction in manufacturing sites. In future studies, it is necessary to develop more efficient and reliable inspection technology through system optimization and performance improvement.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.1
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• pp.31-35
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• 2010

This paper presents the development of automatic defect detection program using 3D computed tomography image of small solid rocker motor. We applied the neighbor pixel comparison algorithm with beam hardening correction for the recognition of defect. We made the artificial defect specimen in order to decide a standard CT value of defect. The program was tested with 150 small solid rocket motors and it could detect the disbond, crack, foreign material and void. The program showed more reliable and faster results than human inspector's interpretation.

• Food Science of Animal Resources
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• v.36 no.2
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• pp.206-214
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• 2016

The aim of this study was to evaluate the potential use of fatty acids, triacylglycerols, and cholesterol in the detection of adulterated milk fat. The fatty acid, triacylglycerol, and cholesterol profiles of the mixtures of milk and non-milk fat (adulteration ratios of 10%, 30%, 50%, 70%, and 90%) were analyzed by gas chromatography. The results showed that concentrations of the fatty acids with oleic acid (C18:1n9c) and linoleic acid (C18:2n6c), triglycerides with C52 and C54, and cholesterol detected are proportional to the adulteration ratios remarkably. Oleic acid (C18:1n9c), linoleic acid (C18:2n6c), C52, and C54 were lower in pure milk fat than in adulterated mixtures. In contrast, pure milk has a higher cholesterol concentration than all adulterated mixtures (adulteration concentration in the range 10-90%). Thus, we suggest that oleic acid (C18:1n9c), linoleic acid (C18:2n6c), C52, C54, and cholesterol are suitable indicators and can be used as biomarkers to rapidly detect adulterated milk fat by gas chromatography. This study is expected to provide basic data for adulteration and material usage. Moreover, this new approach can detect the presence of foreign oils and fats in the milk fat of cheese and can find application in related studies.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.5
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• pp.533-540
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• 2016

This study assessed the risk of an oyster-shucking site to establish the hazard analysis critical control point (HACCP) system model by measuring viable cell counts, coliform group Staphylococcus aureus foreign material on oysters, oyster-producing equipment, and washing water. The viable cell count and coliform group levels of the harvested raw oysters were 4.00 log CFU/g and 1.1×10² MPN/100 g, while those of washed oysters were 2.99 log CFU/g and (3.2−4.6) × 10 MPN/100 g, respectively. After washing the oysters, no Escherichia coli or pathogenic bacteria (E. coli O157:H7, Listeria monocytogenes, S. aureus, Salmonella spp., Vibrio parahaemolyticus, and Clostridium perfringens) were detected. Regardless of the location of foreign matter, up to 100% more metallic and non-metallic foreign matter was detected at 1.5 mmΦ than at 3.5 mmΦ, using a metal detector with increased sensitivity. According to the results, the critical control points (CCP) are the washing and metal-detection processes. These results can be used as basic data to improve sanitation at oyster-shucking sites in factories with an HACCP system.