• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.37-45
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• 2002

A method of measuring the length of defects on the wall and restructuring the defect image is proposed based on the estimation algorithm of a camera orientation, which uses the declination angle of a laser slit beam. The estimation algorithm of the horizontally inclined angle of CCD camera adopts a 3-dimensional coordinate transformation of the image plane where both the laser beam and the original image of the defects exist. The estimation equation is obtained by using the information of the beam projected on the wall and the parameters of this equation are experimentally obtained. With this algorithm, the original image of the defect can be reconstructed as an image normal to the wall. From the result of a series of experiments, the measuring accuracy of the defect is measured within 0.5% error bound of real defect size under 30 degree of the horizontally inclined angle. The proposed algorithm provides the method of reconstructing the image taken at any arbitrary horizontally inclined angle as the image normal as the wall and thus, it enables the accurate measurement of the defect lengths by using a single camera and a laser slit beam.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.2
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• pp.82-88
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• 2017

There are main issues of defect type that condensation, concrete crack and noise in apartment buildings. Especially, according to the Apartment Defect Dispute Mediation Committee in Korea (ADDMC) at Ministry of Land Infrastructure and Transport in Korea (MLIT), condensation defects are great importance (14 percent) on whole number of reported cases of faults from 2015 in Korea. Most condensation defects have many different causes that take a toll on the resident's life and space. So it is very important to early detection and repair. For preventing the condensation in apartment buildings, there are building codes in Korea such as 'Standard of Method and Judgment for Apartment defect of investigation, Repair cost Estimate'. This research aims to study on the improvement of preventing the condensation aforementioned korea standard. Types and characteristics (opaque wall, windows, doors) of cause of occurrence and existing state condensation defect is analyzed from evaluation of real application 100 case in 2015 ADDMC data.

• Journal of Ocean Engineering and Technology
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• v.1 no.2
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• pp.74-82
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• 1987

This study has been made to investigate into the behavior of fatigue limit, of fatigue crack initiation, and of fatigue crack propagation under the condition of rotating bending stress; specifically on the independency of stress field as well as the crack behavior of surface micro hole defect, which is made artificially through the specimen. The results obtained can be summarized as followa; 1) For the single micro hole defect, initiation of fatigue crack is occurred at both tips of microhole defect simultaneosly along the slip which are produced in the range of maximum principal stress arround micro hole defect independent of the size of micro hole defect. 2) For the neighbored deuble micro hole defects with equal size, in the range ($\frac{L}{r}$)ratio $\gtrsim$ 3 defined as the size of micro hole defect(2r) to the distance between the centers of micro hole defects (2L), the crack behavior of the micro hole defects is same as single one. However, for the range of $\frac{L}{r}$<3, the interference effect becomes significant as the ratio approaches to 1.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.129-138
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• 2022

Collecting and labeling sufficient training data, which is essential to deep learning-based visual inspection, is difficult for manufacturers to perform because it is very expensive. This paper presents a steel plate surface defect detection system with industrial-grade detection performance by training a small amount of steel plate surface images consisting of labeled and non-labeled data. To overcome the problem of lack of training data, we propose two data augmentation techniques: program-based augmentation, which generates defect images in a geometric way, and generative model-based augmentation, which learns the distribution of labeled data. We also propose a 4-step semi-supervised learning using pseudo labels and consistency training with fixed-size augmentation in order to utilize unlabeled data for training. The proposed technique obtained about 99% defect detection performance for four defect types by using 100 real images including labeled and unlabeled data.

• Tribology and Lubricants
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• v.40 no.4
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• pp.133-138
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• 2024

This study evaluates the structural safety of wind turbine blades, analyzes the behavior of composite laminate structures with and without defects, and assesses surface erosion wear. The NREL 5 MW standard is applied to assign accurate composite material properties to each blade section. Modeling and analysis of the wind turbine blades reveal stable behavior under individual load conditions (gravity, motor speed, wind speed), with the web bearing most of the load. Surface erosion wear analysis in which microparticle impacts are simulated on the blade coating shows a maximum stress and maximum displacement of 14 MPa and 0.02 mm, respectively, indicating good initial durability, but suggest potential long-term performance issues due to cumulative effects. The study examines defect effects on composite laminate structures to compare the stress distribution, strain, and stiffness characteristics between normal and cracked states. Although normal conditions exhibit stable behavior, crack defects lead to fiber breakage, high-stress concentration in the vulnerable resin layer, and decreased rigidity. This demonstrates that local defects can compromise the safety of the entire structure. The study utilizes finite element analysis to simulate various load scenarios and defect conditions. Results show that even minor defects can significantly alter stress distributions and potentially lead to catastrophic failure if left unaddressed. These findings provide valuable insights for wind turbine blade safety evaluations, surface protection strategies, and composite structure health management. The methodology and results can inform the design improvements, maintenance strategies, and defect detection techniques of the wind energy industry.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.139-143
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• 2011

The problem of delamination of composite tubes by impact has been acknowledged in aerospace and automobile industry. Non-destructive testing(NDT) methods in composite material structure are important to evaluate reliability of composite structure. There are many kinds of NDT methods which can detect the inside defect of the composite material such as Infrared Thermography(IRT). Infrared thermal imaging of object is different from that of a defect, in heated composite tubes with an internal defect, and then location and size of a defect can be measured by the analysis of thermal imaging pattern. In this study, Lock-in Infrared thermography detect internal defects of Impacted composite tubes by the inspection of infrared lay radiated from the surface of composite tubes.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.142-150
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• 2011

Defect dispute has been increasing to claim by condominium, in increasing to demand and concern in value, quality, and management of apartment building since 2000s. In this study, for checking property of cost in crack issue with precedure of lawsuit on defect, it is analyzing details about repairing cost of concrete crack defect that formed 77 percent of repairing cost. Futhermore, it is studying of composition of repairing cost and difference of repairing cost by repairing method. This is checking details that cost growth has a difference whether court accept a acceptable range of crack width, and repairing method and reinforcement work has to choose between a surface treatment method, a filling method and a injecting method. Meanwhile, it is considerable that disparity of repairing cost whether is a method of painting work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.683-688
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• 2015

Recently, various static analysis tools for software defect detection are becoming widely used in practice. However, there is little public information of the most frequent defects in commercial areas until now. In this paper, we analyze the defects found by CodeSonar, a static analysis tool that finds defects in C/C++, Java programs. So we report the most frequent defects by various aspects in Dongnam area, Korea.

• Steel and Composite Structures
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• v.29 no.5
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• pp.647-657
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• 2018

Geometric imperfections may be created during the production process or setting borders of single-layer graphene sheets (SLGSs). Vacancy defects are an instance of geometric imperfection, so investigating the effect of these vacancies on the mechanical properties of single-layer graphene is extremely important. Since very few studies have been conducted on the structure of imperfect graphene (with the vacancy defect) as an anisotropic structure, further study of this defective structure seems imperative. Due to the vacancy defects and for the proper assessment of mechanical properties, the graphene structure should be considered anisotropic in certain states. The present study investigates the effects of site and size of vacancy defects on the mechanical properties of graphene as an anisotropic structure using the lekhnitskii interaction coefficients and Molecular Dynamic approach. The effect of temperature on the severity of the SLGS becoming anisotropic is also investigated in this study. The results reveal that the amount of temperature has a big effect on the severity of the structure getting anisotropic even for a graphene without any defects. The effect of aspect ratio, temperature and also size and site of vacancy defects on the material properties of the graphene are studied in this research work. According to the present study, using material properties of flawless graphene for imperfect structure can lead to inaccurate results.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.5
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• pp.383-392
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• 2007

In this paper, we study the prediction of depth and width of a defect in steam generator tube in nuclear power plant using neural network. To this end, we first generate eddy current testing (ECT) signals for 4 defect patterns of SG tube: I-In type, I-Out type, V-In type, and V-Out type. In particular, we generate 400 ECT signals for various widths and depths for each defect type by the numerical analysis program based on finite element modeling. From those generated ECT signals, we extract new feature vectors for the prediction of defect size, which include the angle between the two points where the maximum impedance and half the maximum impedance are achieved. Using the extracted feature vector, multi-layer perceptron with one hidden layer is used to predict the size of defects. Through the computer simulation study, it is shown that the proposed method achieves decent prediction performance in terms of maximum error and mean absolute percentage error (MAPE).