• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.1-6
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• 2010

Ball bearings are one of main components that support the rotational shaft in high speed rotary machinery. So, it is very important to detect the incipient faults and fault growth of bearing since the damage and failure of bearing can cause a critical failures or accidents of machinery system. In the past, many researchers mainly performed to detect the bearing fault using traditional method such as wavelet, statistics, envelope etc in vibration signals. But study on the detection technique for bearing fault growth has a little been performed. In this paper, we verified the possibility for monitoring of fault growth and detection of fault size in bearing outer-race by using the envelope powerspectrum and probabilistic density function from measured vibration signals.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1847-1853
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• 2008

This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis to demonstrate convergence property of the proposed estimation by using statistical convergence and system stability theory. We apply our fault diagnosis approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.192-200
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• 2001

As the high density memory is widely used in the various applications, the need for reproduction of memory is increased. In this paper we propose an efficient fault diagnosis algorithm of linear order O(n) that enables the reproduction of memory. The new algorithm can distinguish various fault models and identify all the cells related to the faults. In addition, a new BIST architecture for fault diagnosis is developed. Using the new algorithm, fault diagnosis can be performed efficiently. And the performance evaluation with previous approaches proves the efficiency of the new algorithm.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Progress in Superconductivity and Cryogenics
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• v.6 no.3
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• pp.44-49
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• 2004

As the load density of KEOCO system is higher, the fault current can be much higher than SCC(Short Circuit Capacity) of circuit breaker. Fault current exceeding the rating of circuit breaker is a very serious problem in high density load area, which can threaten the stability of whole power system. Even though there are several alternatives to reduce fault current, as the superconductivity technology has been developed, the HTS-FCL(High Temperature Superconductivity Fault Current Limiter) can be one of the attractive alternatives to solve the fault current problem. This study presents the application of 154kV HTS-FCL in Korean power system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.661-669
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• 2004

As the load density of KEPCO system is higher, the fault current can be much higher than SCC(Short Circuit Capacity) of circuit breaker. Fault current exceeding the rating of circuit breaker is a very serious problem in high density load area, which can threaten the stability of whole power system. Even though there are several alternatives to reduce fault current, as the superconductivity technology has been developed, the HTS-FCL (High Temperature Superconductivity Fault Current Limiter) can be one of the attractive alternatives to solve the fault current problem. This study presents the application plication of 154kV HTS-FCL in Korean power system.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1566-1574
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• 2017

When the inter-turn short circuit (ITSC) fault occurs, the distortion of the magnetic field is serious. The motor loss variations of each part are obvious, and the motor temperature field is also affected. In order to obtain the influence of the ITSC fault on the motor temperature distribution, firstly, the normal and the fault finite element models of the permanent magnet synchronous motor (PMSM) were established. The magnetic density distribution and the eddy current density distribution were analyzed, and the mechanism of loss change was revealed. The effects of different forms and degrees of the fault on the loss were obtained. Based on the loss analysis, the motor temperature field calculation model was established, and the motor temperature change considering the loop current was analyzed. The influence of the fault on the motor temperature distribution was revealed. The sensitivity factors that limit the motor continuous operation were obtained. Finally, the correctness of the simulation was verified by experiments. The conclusions obtained are of great significance for the fault and high temperature demagnetization of the permanent magnet analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.537-543
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• 2003

Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

• Journal of the Korea Safety Management & Science
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• v.11 no.1
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• pp.87-91
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• 2009

본 논문은 상대적으로 새로운 기법인 Parzen Density Estimation과 Multi-class SVM을 이용한 지능형 고장 탐색과 진단 방법을 제안하고 있다. 본 연구에서는 롤링 베어링을 대상으로 고장을 탐색하고 진단하기 위한 방법을 제안하는데 Parzen Density Estimation과 Multi-class SVM은 고장 클래스를 잘 표현할 수 있다. Parzen Density Estimation은 새로운 패턴 데이터의 거절과 알려진 데이터 패턴의 밀도의 평가에 의해 새로운 패턴을 찾아낼 수 있고, Multi-class SVM 기반의 방법은 여러 클래스의 고장을 support vector로 표현하여 고장 패턴을 찾아낼 수 있다. 본 연구에서는 실제의 다중 클래스를 가지는 롤링 베어링의 고장 데이터를 사용하여 고장 패턴을 탐색하는 과정을 보여주는데, 커널함수의 적절한 파라미터의 선택에 의한 Multi-class SVM 기반의 방법이 multi-layer perceptron이나 Parzen Density Estimation 방법보다 우수함을 입증한다.

• Progress in Superconductivity and Cryogenics
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• v.4 no.1
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• pp.55-60
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• 2002

$100 A/mm^2$ class Bi-2223 tapes have recently become commercially available. Some important characteristics of the tapes, e .g. critical current, ac loss, characteristics at joint, fault current characteristics, are required for an application such as a power cable or a power transformer. In this paper they have been investigated experimentally. The results indicate that the self-field loss of the high current density tapes is not negligible, compared to resistive loss in a copper wire for the same currents. In a cable, the self-field loss for relatively large currents is much larger than the magnetization loss due to an external field. But in a transformer, the magnetization loss is dominant, compared to the self-field loss. Finally the fault current characteristics show that the high current density tapes are never safe from burn-out even for fault currents with a few cycles.