• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.714-716
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• 1997

In order to prevent the belt from being damaged by metal pieces, we developed multicoil-type metal detection system. This detects the presence of belt clips and position of metal pieces in ores being transported on conveyor belt. In this research, our coil sensor of multicoil-type metal detection system is divided into two parts, exciting part (transmitter coil) and sensing part composed of two receiver coils. Each receiver coil has several coils in the direction of belt width. Multicoil-type metal detection system is operated by supplying a transmitter coil with electric power resources to generate magnetic field, and then the change of magnetic flux resulted from a metal piece on the conveyor be a is induced into sensing coils. We can prevent detector from failing to catch metal pieces due to high threshold level produced by steel belt clips and male the sensitivity of belt-width direction uniform by using multicoil-type metal detection system. Besides, this developed system can recognize precise position and size of metal piece. The experiments shows that our multicoil-type metal detection system has better performances than the conventional metal piece detector.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.120-125
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• 2014

Conventional handheld metal detectors use a single induction coil to detect the metallic parts of explosive objects, and the detector generates an acoustic signal from its magnetic response to a metallic object so that an operator can confirm the existence of mines. Though metal detectors have very useful detection mechanisms to find mines, it is easy to cause a high false alarm ratio due to the detection of non-explosive metallic items such as cans, nails and other pieces of metal, etc. Also, because of the physical characteristic of a metal detector it is hard to detect non-metallic objects such as mines made of wood or plastic. Furthermore, the operator must move it to the left and right slowly and repeatedly to attain enough sensor signals to confirm the existence of mines using only a monotonous acoustic signal. To resolve the disadvantages of handheld detectors, many new approaches have been attempted, such as an arrayed detector and a visualization algorithm based on metal/non-metal sensor. In this paper, we introduce a visualization algorithm with a metal/non-metal complex sensor, an arrayed metal/non-metal sensor and the their testing and evaluation.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.161-166
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• 2014

This Electromagnetic metal piece detection sensor, having high sensitivity even under high humidity and dust density, using LVDT was investigated. Metal detection characteristics using phase detection method, for 3 frequencies covering ELF and LF band, were experimentally measured. It was found that the sensitivity for metal and animal food, in which metal piece was included, was exponentially increased as frequency increased. Reducing cutoff frequency of LPF after PD was found to be effective to proportionally increase sensitivity. Also the sensitivity of metal piece detection was enhanced by optimizing BPF bandwidth and SNR. Metal piece detection limit using available ferrous test samples was found to be 0.7mm diameter from the experiment using 50kHz, in ELF band, which was known to have better selectivity to animal food. is an example of ABSTRACT format.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1183-1188
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• 2011

The novel metal position detection method is proposed where conventional techniques, in high temperature, moisture and particle environment, are not able to be applied. It is known that electronic devices, utilizing microwave, ultrasonic or optical technique, are hard to apply for sensing application where temperature is exceeding above 300 degree centigrade. Metal position detection technique, which was consisted with passive elements facing hot sensing surface, utilizing electromagnetic wave was investigated, and the metal detection sensitivity was measured by varying sensor frequency and sensing distance. Measurement result in laboratory test set-up showed position measurement resolution up to 1mm, when distance between two sensing elements were 500mm, and possibility to measure position of hot metal sheet having very high surface temperature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.865-870
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• 2018

A machine vision based industrial inspection includes defects detection and classification. Fast inspection is a fundamental problem for many applications of real-time vision systems. It requires little computation time and localizing defects robustly with high accuracy. Deep learning technique have been known not to be suitable for real-time applications. Recently a couple of fast region-based CNN algorithms for object detection are introduced, such as Faster R-CNN, and YOLOv2. We apply these methods for an industrial inspection problem. Three CNN based detection algorithms, VOV based CNN, Faster R-CNN, and YOLOv2, are experimented for defect detection on metal surface. The results for inspection time and various performance indices are compared and analysed.

• Bulletin of the Korean Chemical Society
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• v.18 no.3
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• pp.316-318
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• 1997

A general and universal detection method, which can be used in high performance liquid chromatography (HPLC) and flow injection analysis (FIA) system for the determination of any metal ions complexing with ethylenediaminetetraacetic acid (EDTA), is demonstrated. Pulsed amperometric detection scheme is applied in a flow-through thin layer electrochemical cell at an Au working electrode. Fluctuation of peak current level at the same flow rate of carrier solution is minimized at this solid working electrode, whereas not at a dropping mercury electrode. Removal of dissolved oxygen can be omitted with this detection method, which is a required step for cathodic detection methods. Also, a group of metal ions can be determined selectively and indirectly with this detection scheme.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.87-87
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• 2013

The interface between nanomaterials and biosystems is emerging as one of the broadest and most dynamic areas of science and technology, bringing together biology, chemistry, physics and many areas of engineering, biomedicine. The combination of these diverse areas of research promised to yield revolutionary advances in healthcare, medicine, and life science. For example, the creation of new and powerful nanosensors that enable direct, sensitive, and rapid analysis of biological and chemical species can advance the diagnosis and treatment of disease, discovery and screening of new drug molecules. Nanowire based sensors are emerging as a powerful and general platform for ultrasensitive and multiplex detection of biological and chemical species. Here, we present the studies about noble metal nanowire sensors that can be used for sensitive detection of a wide-range of biological and chemical species including nucleic acids, proteins, and toxic metal ions. Moreover, the optical and electrochemical applications of noble metal nanowires are introduced. Noble metal nanowires are successfully used as plasmonic antennas and nanoelectrodes, thereby provide a pathway for a single molecule sensor, in vivo neural recording, and molecular injection and detection in a single living cell.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.600-602
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• 2019

Metals are used in a variety of industrial sites and daily life. Metals are often used in machinery, automobile parts, wires, and robots. Metal causes small damage to the metal surface for a variety of reasons, such as the processing process and the user's operating environment. In this paper, phase detection for the inspection of defects in metals has been implemented. Using the electrical conductivity of metal, a circuit whose phase varies with the depth and size of the defect, and with the changed phase, the depth and size of the defect can be estimated.

• Structural Monitoring and Maintenance
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• v.9 no.3
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• pp.221-235
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• 2022

Among nondestructive damage detection methods, impedance-based methods have been recognized as an effective technique for damage identification in many kinds of structures. This paper proposes a method to detect cracks in metal structures by combining electro-mechanical impedance (EMI) responses and artificial neural networks (ANN). Firstly, the theories of EMI responses and impedance-based damage detection methods are described. Secondly, the reliability of numerical simulations for impedance responses is demonstrated by comparing to pre-published results for an aluminum beam. Thirdly, the proposed method is used to detect cracks in the beam. The RMSD (root mean square deviation) index is used to alarm the occurrence of the cracks, and the multi-layer perceptron (MLP) ANN is employed to identify the location and size of the cracks. The selection of the effective frequency range is also investigated. The analysis results reveal that the proposed method accurately detects the cracks' occurrence, location, and size in metal structures.