• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.64-70
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• 2005

In this literature, fault detection and classification of faulty induction motors are carried out through Z-index and frequency analysis. Above frequency analysis refer Fourier transformation and Wavelet transformation. Z-index is defined as the similar form of energy function, also the faulty and healthy conditions are classified through Z-index. For the detection and classification feature extraction for the fault detection of an induction motor is carried out using the information from stator current. Fourier and Wavelet transforms are applied to detect the characteristics under the healthy and various faulty conditions. We can obtain feature vectors from two transformations, and the results illustrate that the feature vectors are complementary each other.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.6
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• pp.413-422
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• 2022

In this paper, the fault analysis of the momentum wheel, which is a high-speed rotary machinery of 'Control Moment Gyro' for medium and large satellite, was described. For fault diagnosis, envelope spectrum analysis was performed using Hilbert transformation method and signal demodulation method to find the impact signals periodically generated from amplitude modulated signals. Through this, the fault of the momentum wheel was diagnosed by analyzing whether there was a harmonic component of the rotational frequency and a bearing fault frequency in a specific frequency band with a high peak.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1492-1501
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• 2011

A wide-area protection intelligent technique has been used to improve a reliability in power systems and to prevent a blackout. Nowadays, voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in power systems. As this technique has the difficulties in collecting and sharing of information, there have been used a FNET method for the wide-area intelligent protection. This technique is very useful for the prediction of the inception fault and for the prevention of fault propagation with accurate monitoring frequency and frequency deviation. It consists of FDRs and IMS. It is well known that FNET can detect the dynamic behavior of system and obtain the real-time frequency information. Therefore, FDRs must adopt a optimal frequency estimation method that is robust to noise and fault. In this paper, we present comparative studies for the frequency estimation method using IRDWT(improved recursive discrete wavelet transform), for the frequency estimation method using FRDWT(fast recursive discrete wavelet transform). we used the Republic of Korea 345kV power system modeling data by EMTP-RV. The user-defined arbitrary waveforms were used in order to evaluate the performance of the proposed two kinds of RDWT. Also, the frequency variation data in various range, both large range and small range, were used for simulation. The simulation results showed that the proposed frequency estimation technique using FRDWT can be the optimal frequency measurement method applied to FDRs.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2149-2151
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• 2004

The time-frequency domain reflectometry(TFDR) is well known to detect and locate a fault in a coaxial cable[3]. Traditional reflectometry methods have been achieved in either the time domain or frequency domain only. However, the time-frequency domain reflectometry utilizes time and frequency information of a reflected signal passed through a cable to detect and locate the fault. The purpose of this paper is to find appropriate time-frequency distribution function suitable for a TFDR system. Choosing the appropriate time-frequency distribution function implies one can detect the fault and estimate the location accurately. We consider and compare adequate time-frequency distribution function on the basis of experimental results.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.213-217
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• 2008

The flux-lock type superconducting fault current limiter(SFCL) can apply the magnetic field into the high-$T_C$ superconducting(HTSC) element by adopting the magnetic field coil in its third winding. To apply the magnetic field into the HTSC element effectively, the capacitor for LC resonance is connected in series with the magnetic field coil. However, the current waveform of third winding for the application of the magnetic field is affected by the LC resonance condition for the frequency of the source voltage and can affect the waveform of the limited fault current. In this paper, the current waveform of the third winding in the flux-lock type SFCL according to LC resonance condition during a fault period was analyzed. From the differential equation for its electrical circuit, the current equation of the third winding was derived and described with the natural frequency and the damping ratio as design parameters. Through the analysis according to the design parameters of the third winding, the waveform of the limited fault current was confirmed to be influenced by the current waveform of the third winding and the design condition for the stable fault current limiting operation of this SFCL was obtained.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.71-79
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• 2015

Recently, new Low Voltage DC (LVDC) power distribution systems have been constantly researched as uses of DC in end-user equipment are increased. As in conventional AC distribution system, High Impedance Fault (HIF) which may cause a failure of protective relay can occur in LVDC distribution system as well. It, however, is hard to be detected since change in magnitude of current due to the fault is too small to detect the fault by the protective relay using overcurrent element. In order to solve the problem, this paper presents an algorithm for detecting HIF using accumulated energy in LVDC distribution system. Wavelet Singular Value Decomposition (WSVD) is used to extract abnormal high frequency components from fault current and accumulated energy of high frequency components is considered as the element to detect the fault. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed algorithm using ElectroMagnetic Transient Program (EMTP) software. Simulation results considering various conditions show that the proposed algorithm can be utilized to effectively detect HIF.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1079-1088
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• 2003

In this paper, we propose a high-resolution time-frequency domain reflectometry technique as a methodology of detection and estimation of faults on a wire. This method adopts the time-frequency cross correlation characteristics of the observed signal in both time and frequency domains simultaneously. The accuracy of the proposed method is verified with experiments using a RG type coaxial cable and comparing it with traditional time domain as well as frequency domain reflectometry methods. It is clearly shown here that the proposed algorithm produces excellent results compared to the conventional methods for single as well as multiple fault cables.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.819-825
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• 2007

In this paper, we propose a fault diagnosis algorithm of induction motors by DFT and wavelet. We extract a feature vector using a fault pattern extraction method by DFT in frequency domain and wavelet transform in time-frequency domain. And then we deal with a fusion algorithm for the feature vectors extracted from DFT and wavelet to classify the faults of induction motors. Finally, we provide an experimental results that the proposed algorithm can be successfully applied to classify the several fault signals acquired from induction motors.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.510-514
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• 2011

To detect the insulator in the fault state on the electric poles, we first measured radiation sounds from normal state insulators and error state insulators in the anechoic chamber. We processed the signals in frequency domain to find the features with filter bank, narrow band and wide band analysis. So we could found two apparent results from their frequency spectrums - one was 120Hz harmonic components, the other was high average noise level than normal state ones. Then we also introduced a technique for the direction detection of the fault state insulator using the cross correlation from the three dimensional array microphones. To eliminate the noise signal from unexpected directions, we suggested the zero padding technique in cross correlation function. From these, we could conclude that acoustic fault detection techniques are useful of the detection of insulators' faults and the estimation of the direction of the fault state insulators.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.343-346
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• 2000

When a feedback bridging fault is activated, oscillation may be generated in output signal lines. If the oscillation is generated, the fault may not be detected by logic testing. Thus, in the past we proposed a current sensor to detect feedback bridging faults by supply current testing. The sensor circuit design requires the maximum frequency of oscillation which is generated when feedback bridging fault is excited as a specification. In this paper, an estimation method of the oscillation frequency is proposed. Also, it is shown by some experiments that the frequency obtained by the method can be used for the sensor design.