• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.400-405
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• 2005

The diagnosis of mechanical load and of power transmission system failures is usually carried out through mechanical signals such as vibration signals, acoustic emissions, motor speed envelope. If the mechanical load comes from an electrical machine the mechanical failures could be detected previously. Mechanical rotor imbalances and rotor eccentricities are reflected in electric, electromagnetic and mechanical quantities. Therefore, many surveillance schemes apply to the Fourier spectrum of a line current in order to monitor the motor condition. Due to the interaction of the currents and voltages, both these current harmonics are also reflected by a single harmonic component in the frequency spectrum of the electric power. Motor Current Signature Analysis is the usuful technique to assess machine electrical condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.8
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• pp.615-622
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• 2013

Fast and accurate signature extraction is essential to improve the performance of the payload signature-based traffic analysis methods. However the slow manual process in extracting signatures make difficult to deal with the rapidly changing application in current Internet environment. Therefore, in this paper we propose a system automatically generating signatures from ground-truth traffic data. In addition, we improve the efficiency of signature extraction by recognizing the application protocol using a protocol filters and generating signatures automatically according to the application-specific protocol contents. In order to verify the validity of the system proposed in this paper, we compared the signatures automatically generated from our system with the signatures manually created for a few popular applications.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.103-110
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• 2005

Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different load conditions. Multiple Discriminant Analysis (MDA) and Artificial Neural Networks (ANN) provide appropriate environments to develop such fault detection schemes because of their multi-input processing capabilities. This paper describes two fault detection schemes for broken rotor bar fault detection with multiple signature processing, and demonstrates that multiple signature processing is more efficient than single signature processing.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2004-2010
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• 2022

Quantification of sensitive material is of vital importance when it comes to the movement of nuclear fuel throughout its life cycle. Within the electrorefiner vessel of electrochemical separation facilities, the task of quantifying plutonium by neutron analysis is especially challenging due to it being in a constant mixture with curium. It is for this reason that current neutron multiplicity methods would prove ineffective as a safeguards measure. An alternative means of plutonium verification is investigated that utilizes the (𝛼,n) signature that comes as a result of the eutectic salt within the electrorefiner. This is done by utilizing the multiplicity variable a and breaking it down into its constituent components: spontaneous fission neutrons and (𝛼,n) yield. From there, the (𝛼,n) signature is related to the plutonium content of the fuel.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.189-198
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• 2002

Precoder has been shown to be able to provide source diversity and design flexibility. In this paper we employ precoding techniques for block transmission based on a multirate filterbank structure. To accommodate multiuser communication with variable data rates, different precoders with corresponding coefficients and up/down sampling rates are used. However, due to unknown multipath distortion, different interferences may exist in the received data, such as multiuser interference, intersymbol interference and interblock interference. To estimate channel parameters for a desired user, we employ all structured signature waveforms associated with different symbols of that user and apply subspace techniques. Therefore better performance of channel estimator can be achieved than the conventional subspace method based only on the signature of the current symbol. The delay for that user can also be jointly estimated. Channel identifiability conditions and asymptotic channel estimation error are investigated in detail. Numerical examples are provided to justify the proposed method. gest either multicode (MC) or multiple processing gain (MPG) mechanism [2], while requiring data rates to be integral multiples of some basic low-rate. In order to support variable rate transmission however, a comprehensive scheme needs to be investigated.

• Fashion & Textile Research Journal
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• v.26 no.3
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• pp.265-272
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• 2024

In the current era of rapid digitization of the fashion industry, this study aims to facilitate the digitization of local Hawaiian fashion products. The research compares and analyzes the patterns and colors of digital clothing products sold on Zepeto, a metaverse platform, and those of physical products sold both, online and offline, by six specialized brands with stores in Honolulu, Hawaii, or Hawaiian signature clothing products. The following results were obtained: First, physical products generally display various patterns, such as animals, plants, geography, regions, and beaches. However, the pattern diversity of digital products is relatively limited, with a tendency to focus on plant and animal designs, which are Hawaii's signature patterns. Second, the color analysis results demonstrate that chromatic color groups, such as blue and red, were the most popular in physical products, whereas digital products used mostly green and neutral colors. Considering that physical products are sold both, online and offline, this is presumed to be due to differences in expression techniques and customer responses to digital and physical products, rather than market differences. To facilitate the digitization of Hawaiian local fashion products, a library that accommodates physical products in a variety of patterns and colors must be secured, and continuous modifications must be made to match the overall fashion trends.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.9
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• pp.1100-1106
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• 2012

This paper has presented the analysis of the micro-Doppler signatures scattered from the blades of the rotating propeller using the modified HHT method, one of the joint time-frequency analysis methods. The field scattered from the blade edge of the propeller was calculated using equivalent current method(ECM). After the acquisition of the scattered field data in the time domain, the modified HHT method was applied to analyze the micro-Doppler signature. The analysis results showed not only a good agreement with the realistic dynamic characteristic of the blade but also sinusoidally varing characteristics of the micro-Doppler signatures generated from rotating objects. It could be concluded that the joint time-frequency analysis via the modified HHT provided the discriminative characteristics for recognizing a small aircraft target with small RCS value.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.963-974
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• 2018

With the growing interest in cryptocurrency such as bitcoin, the blockchain technology has attracted much attention in various applications as a distributed security platform with excellent security. However, Cryptojacking, an attack that hijack other computer resources such as CPUs, has occured due to vulnerability to the Cryptomining process. In particular, browser-based Cryptojacking is considered serious because attacks can occur only by visiting a Web site without installing it on a visitor's PC. The current Cryptojacking detection system is mostly signature-based. Signature-based detection methods have problems in that they can not detect a new Cryptomining code or a modification of existing Cryptomining code. In this paper, we propose a Cryptojacking detection solution using a dynamic analysis-based that uses a headless browser to detect unknown Cryptojacking attacks. The proposed dynamic analysis-based Cryptojacking detection system can detect new Cryptojacking site that cannot be detected in existing signature-based Cryptojacking detection system and can detect it even if it is called or obfuscated by bypassing Cryptomining code.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.19-21
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• 2001

Induction motors are a critical component of many industrial machines and are frequently integrated in commercial equipment. The many economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system(motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method is used for induction motor fault diagnosis. This method analyzes the motor's supply current, since this diagnoses the motor's condition. The diagnostic system is constructed by using LabVIEW of National Instruments.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.365-368
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• 2001

The advantage of the squirrel cage induction motor is the brush less rotor. This advantage for operation and maintenance turns out to be a disadvantage for the detection of the cage rotor bar and endring defects, which means that the detection of cage faults is due to the measurement and analysis of only the stator input signals. The monitoring task in an inverter drive is complicated mainly because the voltage and current waveforms are nonsinusoidal and the high dv/dt values from fast switching inverterd distort the measurements. In this paper, we are going to discuss the detection method of broken rotor bar of the inverter fed squirrel cage induction motor by the motor current signature analysis(MCSA) and the opening terminal voltage signal analysis.