• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1055-1056
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• 2013

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.179-186
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. 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 and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.20-29
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• 2014

This research aims to study the new paradigm of NDE measurement which allows the identification of defect locations and sizes of a certain structure by measuring its surface temperature after applying heat. STS which has a certain defect is applied by the heat of 70000W by a heater. Its difference of STS surface temperature is measured by using Infrared thermography. The estimated result of STS experiment and that of theoretical analysis of Flex-PDE are compared and analyzed to diagnose STS defect. Moreover, this study can save time and money and improve accuracy in contrast to the existing ultrasonic NDE experiment. In addition, the new paradigm of NDT/NDE by reverse-engineering will be valid if the data of thermal analysis and temperature distribution from the specifications of many materials is accumulated and verified.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.1
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• pp.21-28
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• 2017

This study was performed to propose the sewer defect scoring, and grading protocols for sewer condition assessment. For this, sewer defect scoring methods were comparatively analyzed and reviewed for four international condition assessment protocols, which are established based on WRc manual. As a result, we proposed a new protocol for sewer condition assessment, in which characteristics of sewer pipes are considered by segment. In reference to the PIM-3, the extent of ground subsidence was adopted to be of importance, and renewal scores increased in accordance with weighting of defects causing structural backfill materials. Also, defect grades of 'Hole' were extended to 5 levels of the grading, and 'Surface Damage' was excluded in defect assessment. The addition of 'Buckling' resulted in reduction of weights in 'Surface Damage' and 'Lining Defects'.

• Journal of Ocean Engineering and Technology
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• v.20 no.6 s.73
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• pp.1-6
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• 2006

Corrosion of reinforcing steel bars is a major concern for ocean engineers when reinforced concrete structures are exposed to marine environments. Evaluating the degree of corrosion and corrosion-induced defects is extremely necessary to pursue a proper retrofit or rehabilitation plan for reinforced concrete structures. A promising inspection should be carried out for the evaluation, otherwise the retrofit or rehabilitation process would be useless. Nowadays, ultrasonic guided wave-based inspection techniques become quite promising for the inspection, mainly because of their long-range propagation capability and their sensitivity to different types of defects or conditions. Evaluating haw the guided waves response to the different types of defects or conditions is quite challenging and important. This study shows how surface conditions of reinforcing bars and a corrosion-induced defect, separation, affect guided wave propagation in reinforced concrete. Experiments and associated signal analysis show the sensitivity of guided waves to the surface conditions, as well as the amounts of separation at the interface between. concrete and steel bar.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.627-632
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• 2016

In this paper, we propose a new vision-based defect inspection system for the surface of hot slabs. To minimize the influence of self-emission from slab surfaces with high temperature, an optic method based on blue LED light and a blue pass filter is proposed. Because the slab surface is partially covered with scales, which are unavoidable oxidized substances caused during manufacturing, it is difficult to distinguish between vertical cracks and scale. In order to resolve this problem and to improve the detection performance, the use of a Gabor filter and dynamic programming are proposed. Finally, the effectiveness of the proposed method is shown by means of experiments conducted on images of hot slabs that were obtained from an actual slab production line.

• Bulletin of the Korean Chemical Society
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• v.35 no.2
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• pp.353-356
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• 2014

We fabricated organic photovoltaic (OPV) based on ZnO ripple structure on indium tin oxide as electron-collecting layers and PTB7-F20 as donor polymer. In addition, atomic layer deposition (ALD) was used for preparing additional ZnO layers on rippled ZnO. Addition of 2 nm-thick ALD-ZnO resulted in enhanced initial OPV performance and stability. Based on photoluminescence results, we suggest that ALD-ZnO layers reduced number of surface defect sites on ZnO, which can act as electron-hole recombination center of OPV, and increased resistance of ZnO towards surface defect formation.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.577-586
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• 2022

Detection and classification of steel surface defects are critical for product quality control in the steel industry. However, due to its low accuracy and slow speed, the traditional approach cannot be effectively used in a production line. The current, widely used algorithm (based on deep learning) has an accuracy problem, and there are still rooms for development. This paper proposes a method of steel surface defect detection combining EfficientNetV2 for image classification and YOLOv5 as an object detector. Shorter training time and high accuracy are advantages of this model. Firstly, the image input into EfficientNetV2 model classifies defect classes and predicts probability of having defects. If the probability of having a defect is less than 0.25, the algorithm directly recognizes that the sample has no defects. Otherwise, the samples are further input into YOLOv5 to accomplish the defect detection process on the metal surface. Experiments show that proposed model has good performance on the NEU dataset with an accuracy of 98.3%. Simultaneously, the average training speed is shorter than other models.

• Journal of the korean Society of Automotive Engineers
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• v.11 no.1
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• pp.51-56
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• 1989

This study was performed to investigate the effect of defect on fatigue strength under the stress of rotary bending. The specimens were made of low carbon steel having artificial microholes, namely, single micro-hole and two adjacent micro-holes as natural defects, and the effects of the diameter of hole and the distance between the holes on fatigue strength have been investigated. The obtained result can be summarized as follows: 1, The critical defect means the largest size of defect that does not affect fatigue limit, and correspondes to the size of defect leading to final fracture under fatigue limit of smooth specimen. The size of defect which has an effect on fatigue limit is larger than that of critical defect. 2, The defect larger than the critical defect affects fatigue strength for as a kind of size effect, and the physical meaning of size effect of defect is considered same as the one of notch effect.

• Journal of the Korean Society for Heat Treatment
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• v.12 no.3
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• pp.215-220
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• 1999

Rotary bending fatigue tests were carried out to investigate the artificial defect sensitivity of fatigue limit in annealed and austempered ductile irons. Artificial defect(hole, diameter${\leq}0.4mm$) machined on specimen surface did not bring about an obvious reduction of fatigue limit in austempered ductile iron as compared with annealed. As a result of investigation on $\sqrt{area}$ c which is the critical artificial defect size. $\sqrt{area}$ c of austempered ductile iron is larger than that of annealed. This means that the crack initiation at artificial defect in austempered ductile iron is more difficult in comparison with annealed. In case that the $\sqrt{area}$ c of artificial defect and graphite nodule are same, the rate of crack initiation for graphite nodule is higher than that of artificial defect.