• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.5
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• pp.351-356
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• 2018

Commonly, a live-line alarm can be used to measure the electric field strength of a high-voltage system to calculate its current, but it is hard to detect the electric field of shielded cables or concealed structures, such as underground distribution cables. Current sensors can detect the magnetic field in a single core wire, but they cannot determine the magnetic field about a double-core wire because the currents flow in opposite directions. Therefore, it is very difficult to detect certain current problems, such as a fault current in an extension line comprised of a double line. In this paper, to ultimately develop a sensor that can detect the current regardless of line conditions, we used a simulation to determine the concentration of the magnetic field dependent on the distribution of the external magnetic field and the path of each line's core.

• Journal of Magnetics
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• v.15 no.4
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• pp.221-224
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• 2010

A laboratory sensor model was designed, constructed, and tested based on a newly proposed working principle of magnetic field detection. The principle of sensing employed a time-coded method in correlation with exploiting the advantageous features of the GMI effect. The sensor demonstrated a sensitivity of $10\;{\mu}s/{\mu}T$ in the field range of ${\pm}100\;{\mu}T$. The sensing element in the form of an amorphous thin wire, $100\;{\mu}m$ in diameter ${\times}50\;mm$ long, was fit into a small field modulation coil of 60 mm length. At a magnetic field modulation in the range of hundreds of Hz, the change in time interval of two adjacent GMI voltage peaks was linearly related to the external magnetic field to be measured. This mechanism improved the sensor linearity of the GMI sensor to better than 0.2% in the measuring range of ${\pm}100\;{\mu}T$.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.1-10
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• 2009

Site characterization for structural stability in rock masses mainly involves the collection of joint property data, and in the current practice, much of this data is collected by hand directly at exposed slopes and outcrops. There are many issues with the collection of this data in the field, including issues of safety, slope access, field time, lack of data quantity, reusability of data and human bias. It is shown that information on joint orientation, spacing and roughness in rock masses, can be automatically extracted from LIDAR (light detection and ranging) point floods using the currently available Split-FX point cloud processing software, thereby reducing processing time, safety and human bias issues.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.19-19
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• 2005

This paper reports a novel magnetic force-based microfluidic immunoassay using microbeads and magnetic nanoparticles. The magnetic force-based immunoassay was devised first and successfully applied to detect the rabbit IgG as the model analyte of microfluidic sandwich immunoassay. The microchannels were fabricated by poly(dimethysiloxane) (PDMS) molding processes and bonded on a slide glass by plasma treatment. At the part of the inlet, sample solution was hydrodynamically focused. The focused microbeads of sample solution were flowed through the 150 ${\mu}m$ width channel of outlet. However, when the microbeads are conjugated with the superparamagnetic nanoparticles under the applied magnetic fields, they will switch their flow path and flow through the 95 ${\mu}m$ width channel of outlet. The movements of microbeads conjugated with magnetic nanoparticles were demonstrated by magnetic field $gradients.^{1)}$ High magnetic field gradients using micro electromagnets could be applied to this detection method for high sensitivity and lower detection limit. In addition, the multiplexed $immunoassay^{2)}$ using an encoded microbead which is immobilized with a certain antibody could be possible using this detection principle.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.105-111
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• 2020

Interest and demand for hydrogen sensors are increasing in the field of H₂ leakage detection during storage/transport/use and detection of H₂ dissolved in transformer oil for safety issues as well as in the field of breath analysis for non-invasively diagnosing a number of disease states for a healthy life. In this study, various ZnO-based sensors were synthesized by controlling the reduction in crystallite size, decoration of Pt nanoparticles, doping of electron donating atoms, and doping of various atoms with different ionic radii. The sensing response of the various prepared ZnO-based nanoparticles and quantum dots (QDs) for 10 ppm H₂ was investigated. Among the samples, the smallest-sized (3.5 nm) In³⁺-doped ZnO QDs showed the best sensing response, which is superior to those in previously reported hydrogen sensors based on semiconducting metal oxides. The higher sensing response of In-doped ZnO QDs is attributed to the synergic effects of the increased number of oxygen vacancies, higher optical band gap, and larger specific surface area.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1819-1823
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• 2005

Incorrect information on public sites can cause serious problem. One of relevant countermeasures against this problem is to detect of buried underground utilities in real time. Although there have been several method to detect of buried underground utilities, such as investigating of gravity and elastic wave and electric field, they have not been so efficient tools. Because it is too expensive and difficult to use. In this paper, magnetic sensors which could provide an easier and more efficient method are used to detect of buried underground utilities. Also fluxgate method of self detection are used. Input signal is used $1\~10kHz$ frequency. Filtering and signal processing of output signal are used labview software. After experiment, detection system of buried underground utilities which used magnetic shows possibility of precise detecting of laying object based on theorectical analysis for electromagnetic field.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1146-1151
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• 2011

There are two methods for train control in information transmission by using track circuit system and installing wayside transmitter. Information signal is transmitted to the on-board antenna by using rails. Continuous information about train intervals, speed and route is received by on-board antenna in AF track circuit system. The information signal is included with carrier wave and received by magnetic coupling in the on-board antenna. Therefore, it is important to define standard current level in the AF track circuit system. When current flowed to rails is low, magnetic sensors are not operated by decreasing magnetic field intensity. Hence, SNR is decreased because electric field intensity is decreased. When the SNR is decreased, there is the serious influence of noise upon demodulation. So, the frequency of information signal is not extracted in frequency response. Thus, it is possible to happen to train accident and delay as the information signal is not analyzed in the on-board antenna. In this paper, standard energy density is calculated by using Parseval's theory in UM71c track circuit. Hence, detection time of information signal is presented.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.317-321
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• 2008

Piping in the Nuclear Power plants (NPP) are mostly consisted of carbon steel pipe. The wall thinning defect is mainly occurred by the affect of the flow accelerated corrosion (FAC) of fluid which flows in carbon steel pipes. This type of defect becomes the cause of damage or destruction of piping. Therefore, it is very important to measure defect which is existed not only on the welding partbut also on the whole field of pipe. Over the years, Infrared thermography (IRT) has been used as a non destructive testing methods of the various kinds of materials. This technique has many merits and applied to the industrial field but has limitation to the materials. Therefore, this method was combined with lock-in technique. So IRT detection resolution has been progressively improved using lock-in technique. In this paper, the quantitative analysis results of the location and the size of wall thinning defect that is artificially processed inside the carbon steel pipe by using IRT are obtained.

• Korean Journal of Computational Design and Engineering
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• v.17 no.3
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• pp.208-215
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• 2012

Augmented reality can help to improve user's engineering abilities such as perception and decision making in industry field. Therefore we have studied on the maintenance-supporting applications for inspectors previously. The advantage of pre-existing marker system is that the making and using are easier than any other feature tracking and detection methods. However it must to be exposed to the sufficient light to be detected by computer image processing. The most of industry field is not in clean environment and there are not sufficient light as well. So, the normal marker system is not appropriated for industrial fields. This paper suggests RFID-based marker system to improve marker-detection ability in our AR maintenance system. RFID is not implemented by image processing but it is implemented by electromagnetic induction. Therefore we could more precisely detect markers even if the environment is low-light intensity condition.