• International Journal of Reliability and Applications
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• v.5 no.1
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• pp.37-46
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• 2004

Coil spring of automobile suspension system is very important to safety and dynamics of passenger car and requires a highly advanced quality control during manufacturing processes. Surface cracks on the coil spring rod produced by mechanical machining and heat treatment may cause a severe accident and large cost to the manufacturer. In order to detect surface cracks of the rod, guided wave technique is applied for a fast total volumetric inspection. Pochhammer equation is studied to investigate the dispersion characteristics of the guided wave in the spring rod and optimal wave modes sensitive to the surface crack are selected experimentally to design the experimental arrangement for the generation of guided wave. Rod samples with different size of artificial axial EDM notch on the surface ranging from 50${\mu}{\textrm}{m}$ to 1 mm are examined by guided wave and inspection results discussed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.80-84
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• 2002

In this study, researchers developed the est algorithm for artificial defects in the semic packages and performed to it by pattern recogn technology. For this purpose, this algorithm was I that researcher made software with matlab. The so consists of some procedures including ultrasonic acquistion, equalization filtering, self-organizing backpropagation neural network. self-organizing ma backpropagation neural network are belong to metho neural networks. And the pattern recognition tech has applied to classify three kinds of detective pa semiconductor packages. that is, crack, delaminat normal. According to the results, it was found estimative algorithm was provided the recognition r 75.7%( for crack) and 83.4%( for delamination) 87.2 % ( for normal).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.91-96
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• 2005

In this study, researchers developed the estimative algorithm for artificial defects in semiconductor packages and performed it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Backpropagation Neural Network. Self-Organizing Map and Backpropagation Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages: Crack, Delamination and Normal. According to the results, we were confirmed that estimative algorithm was provided the recognition rates of $75.7\%$ (for Crack) and $83_4\%$ (for Delamination) and $87.2\%$ (for Normal).

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.331-332
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• 2023

With the aging of buildings, the number and importance of regular inspections of buildings are increasing. The current safety inspection goes through a procedure in which a skilled technician visits an old building, visually checks it, takes a photo, and finally organizes and judges it at the office. For this, field personnel and analysis and review personnel are required. Since the inspection procedure includes taking pictures, a huge amount of data has been accumulated from the time digital photos were used to the present. When a model that can check cracks outside a building is developed using these data, manpower and time required can be greatly reduced. Therefore, this study aims to create a model for classifying cracks that occur outside the building through the artificial intelligence method. The created model can be used as a basic model for determining cracks only by external photography in the future, and furthermore, it can be used as basic data for calculating the size and width of cracks.

• Journal of the Korean Society for Nondestructive Testing
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• v.5 no.2
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• pp.22-33
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• 1986

The application and development of on-line monitoring technology of AE to surveillance of crack propagation will contribute to the structural integrity of reactor pressure vessel and piping system. This research has been performed in order to obtain the evaluation technology for source location of AE and the analysis for the AE signal of the welded specimen. AE is detected by 4-channels AE system during pressurization in small pressure vessels. The cracking of artificial defects can be accurately located and categorized in real time. The welded specimens have more events rate and higher amplitude than the weldless less specimens, and the events rate have a peak around the yield point and just before the failure under tensile test.

• Computers and Concrete
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• v.9 no.3
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• pp.215-226
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• 2012

This article employs Support Vector Machine (SVM) for determination of fracture parameters critical stress intensity factor ($K^s_{Ic}$) and the critical crack tip opening displacement ($CTOD_c$) of concrete. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ${\varepsilon}$-insensitive loss function has been adopted. The results are compared with a widely used Artificial Neural Network (ANN) model. Equations have been also developed for prediction of $K^s_{Ic}$ and $CTOD_c$. A sensitivity analysis has been also performed to investigate the importance of the input parameters. The results of this study show that the developed SVM is a robust model for determination of $K^s_{Ic}$ and $CTOD_c$ of concrete.

• International Journal of Concrete Structures and Materials
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• v.5 no.1
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• pp.29-33
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• 2011

This article employs Least Square Support Vector Machine (LSSVM) for determination of fracture parameters of concrete: critical stress intensity factor ($K_{Ic}^s$) and the critical crack tip opening displacement ($CTOD_c$). LSSVM that is firmly based on the theory of statistical learning theory uses regression technique. The results are compared with a widely used Artificial Neural Network (ANN) Models of LSSVM have been developed for prediction of $K_{Ic}^s$ and $CTOD_c$, and then a sensitivity analysis has been performed to investigate the importance of the input parameters. Equations have been also developed for determination of $K_{Ic}^s$ and $CTOD_c$. The developed LSSVM also gives error bar. The results show that the developed model of LSSVM is very predictable in order to determine fracture parameters of concrete.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.97-98
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• 2023

Recently, the use of digital technology in architectural technology is gradually increasing with the development of various industrial technologies. There are artificial intelligence and drones in the field of architecture, and among them, deep learning technology has been introduced to conduct research in areas such as precise inspection of buildings, and it is expressed in a highly reliable way. When a building is deteriorated, various defects such as cracks in the surface and subsidence of the structure may occur. Since these cracks can represent serious structural damage in the future, the detection of cracks was conducted using artificial intelligence that can detect and identify surface defects by detecting cracks and aging of buildings.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.4 s.148
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• pp.467-475
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• 2006

Fatigue strength of hull structural steel plate, extracted from longitudinal bulkhead of a 17-year-old ore/oil carrier for renewal, was investigated in air and in artificial seawater condition. The surface of the plate was covered with corrosion pits and they proved to be crack initiation sites by fractography using SEM. From this research, it was found that the evaluation method for fatigue strength of virgin mild steel plates in air and in artificial seawater can also be applied to the evaluation of the fatigue strength of mild steel plates those were long-term exposed to a corrosive environment and their surfaces had been rusted intensively.

• Journal of the Korean Institute of Rural Architecture
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• v.21 no.1
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• pp.37-44
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• 2019

Recently, various tourist products using hanok have increased rapidly. In the meantime, there is a steady demand for Hanok architecture. However, there are many negative perceptions about wood deformation and biodeterioration. Wood deformation and biodeterioration are related to moisture content. And the cracks occur in the process of removing water from the wood. Therefore, this study investigates the moisture content and cracks of dried hanok made of wood according to the drying method of wood. Drying methods include natural seasoning and artificial seasoning. There was a difference in moisture removal depending on drying period and method of natural seasoning. Drying time should be about 3 years for natural seasoning, so the moisture content of the wood is stable. In addition, the moisture absorption rate was low even in a humid environment where the voids were removed. However, natural seasoning is time consuming. Artificial seasoning, on the other hand, can quickly remove moisture from the wood and reduce porosity, but it is costly. Cracks that occur during the drying of wood may become problematic in appearance and stability due to wider spacing over time. As a result, the difference in the moisture content of the timber depending on the drying method and drying period of the wood was maintained even after the formation. These gaps appeared to be differences in moisture absorption in a wet environment.