• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1541-1542
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• 2008

In this paper, we introduce a live wire power transmission line fault detection system using time-frequency domain reflectometry(TFDR). The TFDR is known that is more precise method than the other conventional ones. However, the TFDR is generally adopted only in fault detection for communication cable, and dead line power transmission line. Therefore, this paper suggests a TFDR system with coupler which separates 220V, 60Hz signal and TFDR reference signal for implementation the live wire fault detection system. This approach is verified by circuit simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1A
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• pp.1-6
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• 2008

TDM-PON has a disadvantage that entire PON system gets into trouble when only one ONU is out of order and sends optical signal constantly. This paper suggests a scheme to find the fault location. TDMA is impossible when upstream traffic is interrupted by continuous wave signal from a troubled ONU. Therefore, CDMA coding is introduced in separating fault ONUs, and detection algorithm is verified.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2115-2121
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• 2009

This paper proposes the new reclosing scheme considering the recovery time of SFCL in distribution systems which is based on variable dead time control. The main idea is that it uses the carrier signal to distinguish whether the fault is instantaneous or permanent after tripping the line by recloser. The system and SFCL is modeled by using Electromagnetic Transient Program(EMTP) and the validity of the reclosing scheme presented in this paper is analyzed according to the fault resistance, the recovery time of SFCL and the fault clearing time.

• Proceedings of the KIEE Conference
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• summer
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• pp.557-559
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• 2004

The study of applying wavelet transform in power cable system fault location has been recognized by many researchers and investigated. For performance of fault location, the fault generated transients can be captured at one end of the cable or both ends. Between two approaches, single-ended approach is less expensive and more reliable as it doesn't need communication link between the ends of the cable. So, we performs the approach based on the one. In this paper, we are going to introduce a new algorithm to discriminate the transient and the reflected signal using wavelet coefficient. For wavelet transform, the stationary wavelet transform(SWT) is applied instead of conventional DWT because SWT has redundancy properties which is more useful in noisy signal processing.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.8
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• pp.816-827
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• 2009

This paper deals with a bearing faults localization technique based on holographic approach by visualizing sound radiated from the faults. The main idea stems from the phenomenon that bearing faults in a moving vehicle generate impulsive sound. To visualize fault signal from the moving vehicle, we can use the moving frame acoustic holography [Kwon, H.-S. and Kim, Y.-H., 1998, "Moving Frame Technique for Planar Acoustic Holography," J. Acoust. Soc. Am. Vol. 103, No. 4, pp. 1734${\sim}$1741]. However, it is not easy to localize faults only by applying the method. This is because the microphone array measures noise(for example, noise from other parts of the vehicle and the wind noise) as well as the fault signal while the vehicle passes by the array. To reduce the effect of noise, we propose two ideas which utilize the characteristics of fault signal. The first one is to average holograms for several frequencies to reduce the random noise. The second one is to apply the partial field decomposition algorithm [Nam, K.-U., Kim, Y.-H., 2004, "A Partial Field Decomposition Algorithm and Its Examples for Near-field Acoustic Holography," J. of Acoust. Soc. Am. Vol. 116, No. 1, pp. 172${\sim}$185] to the moving source, which can separate the fault signal and noise. Basic theory of those methods is introduced and how they can be applied to localize bearing faults is demonstrated. Experimental results via a miniature vehicle showed how well the proposed method finds out the location of source in practice.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.10
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• pp.965-975
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• 2005

In the case of the fault in stator windings of a high voltage motor. it facilitates certain destructive characteristics in insulations. This will result in a decreased reliability in power supplies and will prevent the generation of electricity, which will result in huge economic losses. This study simulates motor windings using normal windings and four faulty windings for an actual fault in stator winding of a high voltage motor. The partial discharge signals produced in each faulty winding were measured using an 80 PF epoxy/mica coupler sensor. In order to quantified signal waves its a way of feature extraction for each faulty signal, the signal wave of winding was quantified to measure the degree of skewness shape and kurtosis, which are both types of statistical parameters, using a discrete wavelet transformation method for each faulty type. Wave types present different types lot each faulty type, and the skewness and kurtosis also present different quantified values. The result of feature extraction was used as a preprocessing stage to identify a certain fault in stater windings. It is evident that the type of faulty signals can be classified from the test results using faulty signals that were randomly selected from the signal, which was not applied in the training after the training and learning period, by applying it to a back-propagation algorithm due to the supervising and learning method in a neural network in order to classify the faulty type. This becomes an important basis for studying diagnosis methods using the classification of faulty signals with a feature extraction algorithm, which can diagnose the fault of stator windings in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2582-2587
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• 2003

This paper proposes an application of sliding mode observer to the problem of fault detection and reconstruction for descriptor systems with both actuator and sensor faults. In detecting and reconstructing the faults simultaneously, first, we will consider the fault detection problem for sensor fault. The detection of sensor fault is achieved from the design of the matrix which eliminates the influence of actuator fault. Secondly, the sliding mode observer which adds the general full-order observer for descriptor system to feedforward injection map and feedforward compensation signal is designed, and through which the sensor fault is reconstructed. Finally, with the reconstructed sensor fault, and by eliminating differential term of the sensor fault, the actuator fault is detected and reconstructed.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.251-256
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• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.2
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• pp.72-77
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• 2011

In this paper, we propose effective diagnosis algorithm for hub bearing fault in driving vehicle using acceleration signal and wheel speed signal measured in hub bearing unit or knuckle. This algorithm consists of differential, envelope and power spectrum method. We developed diagnosis system for realizing proposed algorithm. This system consists of input device including acceleration sensor and wheel speed sensor, calculation device using Digital Signal Processor (DSP) and display device using Personal Digital Assistant (PDA). Using this diagnosis system, a driver can see hub bearing fault(flaking) from the vibration in driving vehicle. With early repairing, he can keep good ride feeling and prevent accident of vehicle resulting from hub bearing fault.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.505-508
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• 2014

Transmission error (TE) is defined as "the angular difference between the ideal output shaft position and actual position". As TE is one of the major source of the noise and vibration of gears, it is originally studied with relation of the noise and vibration of the gears. However, recently, with the relation of mesh stiffness, TE has been studied for fault detection of spur gear sets. This paper presents a physics-based theory on fault diagnostics of a planetary gear using transmission error. After constructing the lumped parameter model using DAFUL, multi-body dynamics software, we developed a methodology to diagnose the faults of the planetary gear including phase calculation, signal processing. Using developed methodology, we could conclude that TE could be a good signal for fault diagnostics of a planetary gear.