• Journal of the Korean Society for Railway
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• v.10 no.1 s.38
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• pp.1-6
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• 2007

Railway wheels in service are regularly checked by ultrasonic testing, acoustic emission and eddy current testing method and so on. However, ultrasonic testing is sometimes inadequate for sensitively detecting the cracks in railway wheel which is mainly because of the fact of crack closure. Recently, many researchers have actively fried to improve precision for defect detection of railway wheel. The development of a nondestructive measurement tool for wheel defects and its use for the maintenance of railway wheels would be useful to prevent wheel failure. The induced current focusing potential drop(ICFPD) technique is a new non-destructive tasting technique that can detect defects in railway wheels by applying on electro-magnetic field and potential drops variation. In the present paper, the ICFPD technique is applied to the detection of surface and internal defects for railway wheels. To defect the defects for railway wheels, the sensor for ICFPD is optimized and the tests are carried out with respect to 4 surface defects and 6 internal defects each other. The results show that the surface crack depth of 0.5 mm and internal crack depth of 0.7 mm in wheel tread could be detected by using this method. The ICFPB method is useful to detect the defect that initiated in the tread of railway wheels

• Journal of the Korean Society of Safety
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• v.18 no.4
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• pp.98-104
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• 2003

Various nondestructive evaluation (NDE) techniques have been studied to locate steel rebars of dowel, and to detect invisible damage such as voids and cracks inside concrete and debonding between rebars and concrete caused by corrosions and earthquakes. In this study, the aurhors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars of dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna array was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. This paper presents the analytical expressions of numerical focusing procedures for 3D image reconstruction and numerical simulation to study the resolution of the system and the effectiveness of multi-frequency technique. Also, the design of 4?4 antenna array with switching devices is introduced as a preliminary study for the final design of whole array.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.58-63
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• 2022

Recently, the improvement of computational processing ability due to the rapid development of computing technology has greatly advanced the field of artificial intelligence, and research to apply it in various domains is active. In particular, in the national defense field, attention is paid to intelligent recognition among machine learning techniques, and efforts are being made to develop object identification and monitoring systems using artificial intelligence. To this end, various image processing technologies and object identification algorithms are applied to create a model that can identify friendly and enemy weapon systems and personnel in real-time. In this paper, we conducted image processing and object identification focused on tanks among various weapon systems. We initially conducted processing the tanks' image using a convolutional neural network, a deep learning technique. The feature map was examined and the important characteristics of the tanks crucial for learning were derived. Then, using YOLOv5 Network, a CNN-based object detection network, a model trained by labeling the entire tank and a model trained by labeling only the turret of the tank were created and the results were compared. The model and labeling technique we proposed in this paper can more accurately identify the type of tank and contribute to the intelligent recognition system to be developed in the future.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.75-81
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• 2023

Video platforms, including YouTube, have a structure in which the number of video views is directly related to the publisher's profits. Therefore, video publishers induce viewers by using provocative titles and thumbnails to garner more views. The conventional technique used to limit such harmful videos has low detection accuracy and relies on follow-up measures based on user reports. To address these problems, this study proposes a technique to improve the accuracy of filtering harmful media using thumbnails, titles, and audio data from videos. This study analyzed these three pieces of multimodal information; if the number of harmful determinations was greater than the set threshold, the video was deemed to be harmful, and its upload was restricted. The experimental results showed that the proposed multimodal information extraction technique used for harmfulvideo filtering achieved a 9% better performance than YouTube's Restricted Mode with regard to detection accuracy and a 41% better performance than the YouTube automation system.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.2
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• pp.235-246
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• 2023

Neutron resonance transmission technique was applied for assaying isotopic fissile materials produced in the pyro-process. In each process of the pyro-process, a different composition of the fissile material is produced. Simulation was basically performed on ²³⁵U and ²³⁹Pu assay for TRU-RE product, hull waste, and uranium addition. The resonance energies were evaluated for uranium and plutonium in the simulation, and the linearity in the detection response was examined on the fissile content variation. The linear resonance energies were determined for the analysis of ²³⁵U and ²³⁹Pu on the different fissile materials. For enriched TRU-RE assay, the sample condition was suggested; The sample density, content, and thickness are the key factors to obtain accurate fissile content. The detection signal is discriminated for uranium and plutonium in neutron resonance technique. The transmitted signal for fissile resonance has a direct relation with the content of fissile. The simulation results indicated that the neutron resonance technique is promising to analyze ²³⁵U and ²³⁹Pu for various types of the pyro-process material. An accurate fissile assay will contribute toward safeguarding the pyro-processing system.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.4
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• pp.67-77
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• 1995

In modern industry the requirement of automation of manufacturing process increases so that unmanned system has been popular as an ultimate goal of modern manufacturing process. In unmanned manufacturing process the tool fracture is a very serious problem because it results in the damage of workpieces and can stop the operation of whole manufa- turing system. In this study, image processing technique is used to detect the fracture of insert tip of face milling using multi-point-tool. In order to acquire the image information of fracture shape of rotation insert tip. We set up the optical system using a light beam chopper. In this system we can reduce the image degradation generated from stopped image of rotating insert tip using image restoration technique. We calculated the mean square error to diagnose the condition of tool fracture, and determind the criteria of tool fracture using experimental and staticstical method. From the results of this study we've developed non- contact detection technique of tool fracture using image processing method and proposed the fracture direction of automation and unmanned system considering the optimal time of tool change milling.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1101-1105
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• 2011

Radiation particles can introduce temporary errors in memory systems. To protect against these errors, so-called soft errors, error detection and correcting codes are used. In addition, scrubbing is applied which is a fundamental technique to avoid the accumulation of soft errors. This paper introduces an optimal scrubbing scheme, which is suitable for a system with auto error detection and correction logic. An auto error detection and correction logic can correct soft errors without CPU's writing operation. The proposed scrubbing scheme leads to maximum reliability by considering both allowable scrubbing load and the periodic accesses to memory by the tasks running in the system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.646-648
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• 2012

In this paper, an image detection technique is proposed to extract image features in a mobile terminal environment. To detect objects, the HSI color model of the image is used. The object's corner points are detected using the Harris corner detection method. Finally we detect the object of interest using region growing The experiment results show that the proposed method improves detection performance and reduces the amount of computation.

• ETRI Journal
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• v.29 no.2
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• pp.240-242
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• 2007

This letter proposes a simplified maximum likelihood detection (SMLD) scheme to improve the detection performance of multiple-input multiple-output receivers. The SMLD detects V streams according to the first detected V sub-streams. Through an ML test, the most probable stream is selected. Moreover, to detect the layer with the worst post-detection SNR accurately, reverse ordering is applied to the SMLD. Simulation results show that the performance of the Vertical Bell Laboratories layered space-time (V-BLAST) system can be improved by adopting the SMLD technique. In the case of reverse ordering, the SMLD can achieve a similar ML performance with significant reduction in computational complexity.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.102-107
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• 2015

In this paper, we propose a technique of drowsiness detection using a histogram for vehicle safety. The drowsiness of vehicle drivers is often the main cause of many vehicle accidents. Therefore, the checking of eye images in order to detect the drowsiness status of a driver is very important for preventing accidents. In our suggested method, we analyse the changes of a histogram of eye region images which are acquired using a CCD camera. We develop a drowsiness detection system using this histogram change information. The experimental results show that the proposed method enhances the accuracy of detecting drowsiness to nearly 97%, and can be used to prevent accidents due to driver drowsiness.