• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.365-370
• /
• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

• Corrosion Science and Technology
• /
• v.13 no.4
• /
• pp.125-129
• /
• 2014

Shinning spot defects on galvanized steel sheets were studied by optical microscope, scanning electron microscope(SEM), Energy Dispersive Spectrometer (EDS) and Laser-Induced Breakdown Spectroscopy Original Position Statistic Distribution Analysis (LIBSOPA) in this study. The research shows that the coating thickness of shinning spot defects which caused by the substrate defect is much lower than normal area, and when skin passed, the shinning spot defect area can not touch with skin pass roll which result in the surface of shinning spot is flat while normal area is rough. The different coating morphologies have different effects on the reflection of light, which cause the shinning spot defects more brighter than normal area.

• Archives of Craniofacial Surgery
• /
• v.10 no.2
• /
• pp.71-75
• /
• 2009

Purpose: Recently, orbital wall fracture is common injuries in the face. Facial CT is essential for the accurate diagnosis and appropriate treatment to reconstruct of the orbital wall. The objective of this study was to report the method for accurate measurement of area and shape of the bony defect in the blow-out fractures using facial CT in prior to surgery. Methods: The authors experienced 46 cases of orbital wall fractures and examined for diplopia, sensory disturbance in the area of distribution of the infraorbital nerve, and enophthalmos in the preoperation and followed 1 months after surgery, from August 2007 to May 2008. Bony defect was predicted by measuring continuous defect size from 3 mm interval facial CT. Copying from the defect model (template), we reconstructed orbital wall with resorbable sheet (Inion $CPS^{(R)}$ Inion Oy, Tampere, Finland). Results: One months after surgery using this method, 26 (100%) of the 26 patients improved in the diplopia and sensory disturbance in the area of distribution of the infraorbital nerve. Also 8 (72.7%) of the 11 patients had enophthalmos took favorable turn. Conclusion: This accurate and time-saving method is practicable for determining the location, shape and size of the bony defect. Using this method, we can reconstruct orbital wall fracture fastly and precisely.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.21 no.4
• /
• pp.348-353
• /
• 2008

Most of the high voltage insulation systems, such as the power cable joint having hetero interface, are composed of more than two different insulators to improve insulating performance. The partial discharge(PD) in these hetero interface is expected to affect the total insulation performance. Thus, it is important to study electrical properties on these interfaces. This study described the influence of copper and semiconductive substance defects on $\Phi$-q-n distribution between the interface of the model cable joints to classify PD source. PD was sequentially detected for 600 cycles of the applied voltage. The K-means cluster analysis has been analyzed to investigate the $\Phi$-q-n distribution. The skewness-kurtosis(Sk-Ku) plot from K-means clustering results was defined to quantify cluster distribution and classify distribution patterns. The Sk-Ku plot is composed of skewness and kurtosis along abscissa and ordinate which indicate the asymmetry and the sharpness of distribution. As a result of the Sk-Ku plot, it was confirmed that the data was distributed in 1st 2nd and 3rd quadrant at copper foreign substance defect, but in case of semiconductive foreign substance, the data was distributed in 2nd quadrant only.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2007.11a
• /
• pp.203-204
• /
• 2007

This paper investigated the influence on partial discharge distribution of various defects at the model power cable joints interface using K-means clustering. As the result of analyzing discharge number distribution of ${\Phi}-n$ cluster, clusters shifted to $0^{\circ}\;and\;180^{\circ}$ with increasing applying voltage. It was confirmed that discharge quantity and euclidean distance between centroids were increased with applying voltage from the analyzing centroid distribution of ${\Phi}-q$ cluster. The degree of dispersion was increased with calculating standard deviation of ${\Phi}-q$ cluster centroid. The tendency both number of discharge and mean value of ${\Phi}-q$ cluster centroid were some different with defect types.

• Proceedings of the Korean Institute of Surface Engineering Conference
• /
• 2003.05a
• /
• pp.61-61
• /
• 2003

It is important to know SIze distribution of defects In electroplated trivalent chrome layers because it significantly influences on performance of the layers. Most of the nano-scale defects are able to be introduced by hydrogen evolution during the plating. Little information is available on the nano-size defects. In this study, SANS was applied to determine the size distribution of nano-scale defects in the trivalent chrome layers prepared in a formate bath. The defect size and distribution was dependent upon plating conditions such as current density and applied voltage. SANS is one of useful techniques to determine the nano-scale defect in the electroplated layers.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.11
• /
• pp.55-61
• /
• 2009

The wall thinning defect of nuclear power pipe is mainly occurred by the affect of the flow accelerated corrosion (FAC) of fluid. This type of defect becomes the cause of damage or destruction of in carbon steel pipes. Therefore, it is very important to measure defect which is existed not only on the welding part but also on the whole field of pipe. This study use dual-beam Shearography, which can measure the out-of-plane deformation and the in-plane deformation by using another illuminated laser beam and simple image processing technique. And this study proposes Infrared thermography, which is a two-dimensional non-contact nondestructive evaluation that can detect internal defects from the thermal distribution by the inspection of infrared light radiated from the object surface. In this paper, defect of nuclear power pipe were, measured using dual-beam shearography and infrared thermography, quantitatively evaluated by the analysis of phase map and thermal image pattern.

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

• Advances in nano research
• /
• v.16 no.1
• /
• pp.91-109
• /
• 2024

Carbon nanotubes are drawing wide attention of research communities and several industries due to their versatile capabilities covering mechanical and other multi-physical properties. However, owing to extreme operating conditions of the synthesis process of these nanostructures, they are often imposed with certain inevitable structural deformities such as single vacancy and nanopore defects. These random irregularities limit the intended functionalities of carbon nanotubes severely. In this article, we investigate the mechanical behaviour of double-wall carbon nanotubes (DWCNT) under the influence of arbitrarily distributed single vacancy and nanopore defects in the outer wall, inner wall, and both the walls. Large-scale molecular simulations reveal that the nanopore defects have more detrimental effects on the mechanical behaviour of DWCNTs, while the defects in the inner wall of DWCNTs make the nanostructures more vulnerable to withstand high longitudinal deformation. From a different perspective, to exploit the mechanics of damage for achieving defect-induced shape modulation and region-wise deformation control, we have further explored the localized longitudinal and transverse spatial effects of DWCNT by designing the defects for their regional distribution. The comprehensive numerical results of the present study would lead to the characterization of the critical mechanical properties of DWCNTs under the presence of inevitable intrinsic defects along with the aspect of defect-induced spatial modulation of shapes for prospective applications in a range of nanoelectromechanical systems and devices.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2008.10a
• /
• pp.134-137
• /
• 2008

The effects of residual stress and surface defects on the mechanical properties of the high carbon steel filament used for the automotive tire have been experimentally investigated. The samples were fabricated with annealing temperature. The residual stress was measured by focused ion beam and strain mapping software which has advantages, such as data with high accuracy and fast data acquisition time. Mechanical properties, such as tensile strength and fatigue resistance, were gradually increased up to $200^{\circ}C$ and then slightly decreased. From the measurement of residual stress and level of surface defect, it was revealed that the critical factor was varied with different temperature region. That is, the fatigue resistance increased due to decreasing the residual stress and decreased due to increasing the size and distribution of surface defect.