• Proceedings of the KWS Conference
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• 2006.10a
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• pp.283-285
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• 2006

Non Destructive Examination for welds is one of the most important processes to ensure the integrity of facilities of Nuclear power plants. An automated ultrasonic testing program is developed for welding inspection. A test block with side EDM notch is inspected with this program. This paper shows that the developed automated ultrasonic testing program is quite effective.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.946-949
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• 2005

This paper deals with the algorithm development that inspects defects such as Bright Defect Dots, Dark Defect Dots, and Line Defect caused by the process of LCD(Liquid Crystal Display). While most of LCD production process is automated, the inspection of LCD panel and its appearance depends on manual process. So, the quality of the inspection is affected by the condition of worker. Especially, the more LCD size increases, the more the worker feels fatigued, which causes the probability of miss judgement. So, the automated inspection is required to manage the consistent quality of the product and reduce the production costs. In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of LCD. Experimental results reveal that we can recognize various types of defect of LCD with good accuracy and high speed.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.91-101
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• 2016

The automated part quality inspection poses many challenges to the engineers, especially when the part features to be inspected become complicated. A large quantity of part inspection at a faster rate should be relied upon computerized, automated inspection methods, which requires advanced quality control approaches. In this context, this work uses innovative methods in remote part tracking and quality control with the aid of the modern equipment and application of support vector machine (SVM) learning approach to predict the outcome of the quality control process. The classifier equations are built on the data obtained from the experiments and analyzed with different kernel functions. From the analysis, detailed outcome is presented for six different cases. The results indicate the robustness of support vector classification for the experimental data with two output classes.

• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.155-165
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• 2022

As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R²) and 0.980 (R²), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.

• Journal of the Korean Society for Nondestructive Testing
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• v.2 no.1
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• pp.25-30
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• 1982

• The monthly packaging world
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• s.123
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• pp.80-87
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• 2003

• KEPCO Journal on Electric Power and Energy
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• v.6 no.2
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• pp.185-185
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• 2020

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.2
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• pp.255-265
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• 1995

Due to advances in automated manufacturing systems and automatic inspection equipment, complete inspection has drown increased attention recently and has become a widespread practice. In a complete inspection plan all of the items are subject to acceptance inspection If an item fails to meet the predetermined specifications, it is rejected. In this paper, economic complete inspection plans are developed in situations where rejected items are reworked Complete inspections based on the performance variable of interest or a variable which is correlated with the performance variable are considered. Cost models are constructed which involve cost incurred by imperfect quality rework cast and quality inspection cost Methods of finding the optimal complete inspection plans are presented and numerical examples are given.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.1
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• pp.26-33
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• 2013

BMI nozzles in bottom head of the nuclear vessel are one of major components in nuclear power plants. The BMI nozzles have high possibility to generate PWSCC(primary water stress corrosion crack) according to recent foreign case although operation temperature is lower then the upper head of the nuclear vessel. Thus, nondestructive inspection of the BMI nozzles is required. But, inspection of BMI nozzles is not easy since the BMI nozzles placed in high radiated area and inside the nozzles filled with boric acid. Thus, in this study, a TOFD transducer for inspection of BMI and automated scanner system with water were developed. Also, validation of performance of the developed transducer and system are performed using specimens with artificial defects.