• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.623-625
• /
• 2021

Rubber o-rings are produced by conventional injection molding methods. In this case, products that are not normally molded are determined to be defective. However, if images acquired during image-based reading are read as original, there is a problem of poor accuracy. We have thus learned from convolutional neural networks using adaptive binarization and Convex Hull algorithms by extracting only rubber oring parts from the original images through pre-processing. During the test process, it was confirmed that the defect detection performance of the learning method applied pre-processing was better than the standard suggested.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.21 no.6
• /
• pp.650-657
• /
• 2001

This paper explains the process of designing a shielded encircling remote field eddy current (RFEC) probe to inspect nuclear fuel cladding tubes and investigates resulting signal characteristics. To force electromagnetic energy from exciter coil to penetrate into the tube, exciter coil is shielded outside by laminations of iron insulated electrically from each other. Effects of shielding and the proper operating frequency are studied by the finite element analysis and the location for sensor coil is decided. However, numerically simulated signals using the designed probe do not clearly show the defect indication when the sensor passes a defect and the other indication appeared as the exciter passes the defect is affected by the shape of shielding structure, which demonstrates that the sensor is directly affected by exciter fields. For this reason, the sensor is also shielded outside and this shielding dramatically improves signal characteristics. Numerical modeling with the finally designed probe shows very similar signal characteristics to those of inner diameter RFEC probe. That is, phase signals show almost equal sensitivity to inner diameter and outer diameter defects and the linear relationship between phase signal strength and defect depth is observed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.11
• /
• pp.6432-6439
• /
• 2014

The NAUT (Non-contact Air coupled Ultrasonic Testing) technique is one of the ultrasonic testing methods that enables non-contact ultrasonic testing by compensating for the energy loss caused by the difference in acoustic impedance of air with an ultrasonic pulser receiver, PRE-AMP and high-sensitivity transducer. As the NAUT is performed in a state of steady ultrasonic transmission and reception, testing can be performed on materials of high or low temperatures or specimens with a rough surface or narrow part, which could not have been tested using the conventional contact-type testing technique. For this study, the internal defects of spot weld, which are often applied to auto parts, and CFRP parts, were tested to determine if it is practical to make the NAUT technique commercial. As the spot welded part had a high ultrasonic transmissivity, the result was shown as red. On the other hand, the part with an internal defect had a layer of air and low transmissivity, which was shown as blue. In addition, depending on the PRF (Pulse Repetition Frequency), an important factor that determines the measurement speed, the color sharpness showed differences. With the images obtained from CFRP specimens or an imaging device, it was possible to identify the shape, size and position of the internal defect within a short period of time. In this paper, it was confirmed in the above-described experiment that both internal defect detection and image processing of the defect could be possible using the NAUT technique. Moreover, it was possible to apply NAUT to the detection of internal defects in the spot welded parts or in CFRP parts, and commercialize its practical application to various fields.

• Journal of the military operations research society of Korea
• /
• v.37 no.1
• /
• pp.49-70
• /
• 2011

This paper re-evaluated the research on the accounting information's effectiveness in military construction contracts, questioning the former research results on the central army's construction contract that was under the Qualification Assessment System, especially concerning the relations between the accounting information and the bidding ratios as well as the relations between the bidding rates and the defect rates, which targeted between 1 to 10 billions civil engineering, construction, electricity, telecommunication, and environment work types. Unlike the previous results, the relationship between the accounting information and the bidding rates was shown to be considerably limited that the bidding ratio could not be identified through the accounting information, while it could discern the relations with the defect rates. Furthermore, the proven results did not support the hypothesis that the differences in bidding rates could affect the defect ratio. However, through the prediction model of bidding and defect ratios, we could identity the accounting variables that influenced the ratios. Additionally through the results regarding the non-financial indexes in the Pre-Qualification items, the weight on these indexes could be adjusted. In conclusion, the research results has given us new understanding of the problems in the Qualification Assessment System which accounts for the majority of the current military construction contracts and provide validity on the government's expanded implementation of the Lowest Price Award System.

• Archives of Plastic Surgery
• /
• v.44 no.1
• /
• pp.26-33
• /
• 2017

Background The purpose of this study was to assess the correlation between the 2-dimensional (2D) extent of orbital defects and the 3-dimensional (3D) volume of herniated orbital content in patients with an orbital wall fracture. Methods This retrospective study was based on the medical records and radiologic data of 60 patients from January 2014 to June 2016 for a unilateral isolated orbital wall fracture. They were classified into 2 groups depending on whether the fracture involved the inferior wall (group I, n=30) or the medial wall (group M, n=30). The 2D area of the orbital defect was calculated using the conventional formula. The 2D extent of the orbital defect and the 3D volume of herniated orbital content were measured with 3D image processing software. Statistical analysis was performed to evaluate the correlations between the 2D and 3D parameters. Results Varying degrees of positive correlation were found between the 2D extent of the orbital defects and the 3D herniated orbital volume in both groups (Pearson correlation coefficient, 0.568-0.788; $R^2=32.2%-62.1%$). Conclusions Both the calculated and measured 2D extent of the orbital defects showed a positive correlation with the 3D herniated orbital volume in orbital wall fractures. However, a relatively large volume of herniation (>$0.9cm^3$) occurred not infrequently despite the presence of a small orbital defect (<$1.9cm^2$). Therefore, estimating the 3D volume of the herniated content in addition to the 2D orbital defect would be helpful for determining whether surgery is indicated and ensuring adequate surgical outcomes.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.5
• /
• pp.211-220
• /
• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Structural Engineering and Mechanics
• /
• v.20 no.2
• /
• pp.143-160
• /
• 2005

Modal analysis of cracked cantilever composite beams, made of graphite-fibre reinforced polyamide, is studied. By using the finite element and component mode synthesis methods, a numeric model applicable to investigate the vibration of cracked composite beams is developed. In this new approach, from the crack section, the composite beam separated into two parts coupled by a flexibility matrix taking into account the interaction forces. These forces are derived from the fracture mechanics theory as the inverse of the compliance matrix calculated with the proper stress intensity factors and strain energy release rate expressions. Numerical results are obtained for modal analysis of composite beams with a transverse non-propagating open crack, addressing the effects of the location and depth of the crack, and the volume fraction and orientation of the fibre on the natural frequencies and mode shapes. By means of modal data, the position and dimension of the defect can be found. The results of the study confirmed that presented method is suitable for the vibration analysis of cracked cantilever composite beams. Present technique can be easily extended to composite plates and shells.

• Design & Manufacturing
• /
• v.6 no.2
• /
• pp.79-83
• /
• 2012

Inner part is used as an insulator in wire fuses. After injection molding, inner part has been showed flashes, filling defects and deformation. After production, operators have to cut off flashes, one by one. this process leads to continuous low productivity and loss of source materials. This study focuses on identifying the causes for flashes, filling defects, clamping force of injectors, mold adhesion, resin of liquidity and others, and on resolving those issues.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.3
• /
• pp.99-109
• /
• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2006.08a
• /
• pp.491-494
• /
• 2006

A number of research groups and companies have succeeded in employing various SLS schemes to create low defect-density Si films on glass substrates for making high performance TFTs. In this paper, we first point out that SLS can be utilized to just as effectively handle crystallization of thin Si films on polymer substrates, and then present preliminary results on high-performance circuits that are built using the materials.