• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.6
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• pp.128-133
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• 2011

In this study, the steel material for shipbuilding(LR-A class) was used, and FCAW was taken advantage of 3G attitude and they are welded by different welding ways. As a result of analyzing wave with welding monitoring system, the stable values are obtained which are the first floor(electronic current 164~182 A, voltage 24 V), the second floor(electronic current 174~190 A, voltage 22~25 V), the third floor(electronic current 158~188 A, voltage 22~25 V), and fourth floor(electronic current 172~184 A, voltage 22~25 V), at this time, the stable wave standard deviation and changing coefficient could be obtained. When the welding testing through nondestructive inspection was analyzed know defect of welding, there was no defect of welding in A, D, E, but some porosities in B, and slag conclusion near the surface in C, because the length of arc was not accurate, and the electronic current and voltage was not stable. After observing the change of heat affect zone through micro testing, each organization of floor formed as Grain Refinement, so welding part was fine, the distance of heat affect zone is getting wider up to change the values of the electronic current and voltage. As a result of degree of hardness testing, the hardness orders were the heat affect zone(HAZ), Welding Zone(WZ), and Base Metal(BM). When the distribution of degree of hardness is observed. B is the highest degree of hardness The reason why heat effect zone is higher than welding zone and base metal, welding zone is boiled over melting point($1539^{\circ}C$) and it starts to melt after the result of analysis through metal microscope, so we can know that delicate tissue is created at the welding zone. Therefore, in order to get the optimal conditions of the welding, the proper current of the welding and voltage is needed. Furthermore the precise work of welding is required.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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• pp.15-25
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• 2017

The findings were summarized as follows. The safety check by manufacturer showed that 6 of 13 companies are over the average occurrence of defects. It was expected that there would be a difference between manufacturing technology capability and production system of each manufacturer. Consequently, manufacturers should institutionally improve and strengthen certification items for the upward standardization of safety certification before factory. Second, the safety check by year showed that the results of this study accord with those of previous studies on defect time. Consequently, manufacturers should classify the 3-year-old equipment for vehicle-mounted MEWP into a special check subject to do a nondestructive test according to proven results, and also reflect the test in a safety test system to do regular preventive activities of equipment defects. Third, the safety check by part showed that the boom and outrigger parts of vehicle-mounted MEWP have the most defects. Stress concentration resulted in defects as the boom part was most frequently operated in the structural parts for a real work. To prevent this, it is suitable to improve the hardness of boom materials. The outrigger part needs improvement in safety devices with materials. As an outrigger supports the overturning moment of equipment, it is most affected by its load based on the operating radius, resulting in fatigue crack.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2085-2092
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• 2016

One of the most important properties of the IC substrate is that it should be uniform over large areas. Among the various physical approaches of wafer defect characterization, special attention is to be payed to the infrared techniques of inspection. In particular, a high spatial resolution, near infrared absorption method has been adopted to directly observe defects in semi-insulating GaAs. This technique, which relies on the mapping of infrared transmission, is both rapid and non-destructive. This method demonstrates in a direct way that the infrared images of GaAs crystals arise from defect absorption process. A new interpretation is presented for the observed reversal of contrast in the infrared absorption of nonuniformly distributed deep centers, related to EL2, in semi-insulating GaAs. The low temperature photoquenching experiment has demonstrated in a direct way that the contrast inverse images of GaAs wafers arise from both absorption and scattering mechanisms rather than charge re-distribution or local variation of bandgap.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.1
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• pp.53-58
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• 2002

New nondestructive inspection (NDI) technique to detect the defect in metal was developed in which an electromagnetic field is induced in a metal by AC current flowing in the magnetic coil and the leak magnetic-flux disturbed by defects is measured using a tape-recorder head with air gap. This technique can be applied in evaluating the location and sizing of surface defects in components of the ferromagnetic body by means of the non-contacting measurement. In this paper, we have applied this technique to the evaluation of two-dimensional surface cracks in ferromagnetic metal, and also investigated the influence of the various frequencies and lift-off. Defects were detected with maximum values in the distribution of voltage and it was found that the maximum values tend to increase with the defect depth. Although the maximum values for defects are affected by the frequency and lift-off, the depth of small defects can be estimated from the linear relationship between the depth and voltage rate$(V_0/V_{ave})$.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.555-561
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• 2000

The remote field eddy current (RFEC) inspection was performed on the ductile cast iron pipes with nominal outer diameter of 100mm, which were machined with various shapes and sizes of defects. Ductile cast iron pipes which are used as water supply pipe have the non-uniform thickness and asymmetric cross section due to relatively high degree of allowable errors during the manufacturing processes. These characteristics of ductile cast in pipes cause the long range background noises in RFEC signals along the pipe. In this study, tile machined defects in pipes were effectively classified by the moving window average (MWA) method which eliminated the long-range noise. The voltage plane polar plots (VPPP) method was used to quantitatively evaluate the depth and circumferential degree of defects. The VPPP signatures showed that the angle between defect signature and the normalized in-phase component on the VPPP is linear to the depth of defects. The nondestructive RFEC technique proved to be capable of quantitatively evaluating the machined defects of underground water supply pipe.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.15-21
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• 2019

X-rays with shorter wavelengths than ultraviolet light have very good penetration power. It is convergence in industrial and medical fields has been used a lot. n particular, in the industrial field, various researches have been conducted on the detection of foregin body inside metal that can occur in the production process of products such as metal using x-ray, a non-destructive inspection device. Detectors are becoming increasingly popular for the popularization of DR (Digital Radiography) photography methods that digitally acquire X-ray video images. However, there are cases where foreign body detection is impossible depending on the sensor noise and sensitivity inside the detector. When producing a metal product, since the defective rate of the produced product may increase due to contamination of the foreign body, accurate detection is necessary. In this paper, we provide a correction model for X-ray images acquired in order to improve the efficiency of defect detection such as foreign body inside metal. When applied to defect detection in the production process of metal products through the proposed model, it is expected that the detection of product defects can be processed accurately and quickly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.421-431
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• 2009

This paper is the study on the verification of structural health monitoring (SHM) algorithm based on the ultrasonic guided wave. An active inspection system using Lamb wave (LW) for SHM was considered. The basic study about the application of this algorithm was performed for detecting the circular notch defect in steel plate. LW testing technique, pitch-catch method, was used for interpretation of circular notch defect with depth of 50% of plate thickness and 7 mm width. Damage characterization takes place by comparing $S_0$ mode sensor signals collected before and after the damage event. By subtracting the signals of both conditions from each other, a scatter signal is produced which can be used for damage localization. The continuous Gabor wavelet transform is used to attain the time between the arrivals of the scatter and sensor signals. A new practical damage monitoring algorithm, based on damage monitoring polygon and pitch-catch method, has been proposed and verified with good accuracy. The possible damage location can be estimated by the average on calculated location points and the damage extent by the standard deviation.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.69-78
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• 2023

With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.

• Journal of Biosystems Engineering
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• v.36 no.5
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• pp.377-383
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• 2011

This study proposed the new method of discerning the assembled parts and presuming the position of central point in a Cowl Cross Bar (CCB) using a Charge-Couple Device (CCD) camera attached to a robot in the auto assembly line. Three control points of an ellipse were decided by three reference points, which were equally distanced. The radii of these reference points were determined by the size of the object, and the repeated presumption secured the precise determination. The comparison of the central point of ellipse presumed by Randomized Hough Transform (RHT) with the part information stored in a database was used for determining the faulty part in an assembly. The method proposed in this study was applied for the real-time inspection of elliptical parts, such as bolt, nut hole and so on, connected to a CCB using a CCD camera. The findings of this study showed that the precise decision on whether the parts are inferior or not can be made irrespective of the lighting condition of industrial site and the noises of the surface of the part. In addition, the defect decision on the individual elliptic parts assembled in a CCB showed more than 98% accuracy within a 500-millisecond period at most.