• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.185-190
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• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.813-822
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• 2012

Abnormal operating sounds radiated from a moving transfer robot in LCD (liquid crystal display) product lines have been used for the fault detection line of a robot instead of other source signals such as vibrations, acoustic emissions, and electrical signals. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone, despite a relatively low sensitivity. The wavelet packet transform for feature extraction and the artificial neural network for fault classification are employed. It can be observed that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.699-704
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• 2005

In the station of the railway and the subway various illumination equipment and a general power equipment for a passenger convenience, the signal equipment and the communication equipment which is necessary to the train operation provided. At the all of like this equipment from the electric room which is established in each station by changing from high voltage to low voltage and it supplies from the illumination transformer, the power transformer and the signal transformer. If it supplies to the equipment from the high voltage to the low voltage, it must be established to contact protection device in between the high voltage coil and the low voltage coil. Also it must do the grounding faulting device at the low voltage lines, the earthing devices at apparatus for the protection of an electric shock and an electric fire by the electric relation law. Compared the related regulations between the facilities which require protective functions such as grounding fault or earthing in public utilities like subway stations, and the facilities which do not require line earthing or protective functions such as electricity supplied for signalling the train. Also, will describe a countermeasure for the accident from a grounding fault.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.380-387
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• 2010

For the fault diagnosis of three-phase induction motors, we propose a diagnosis algorithm based on mutual information and linear discriminant analysis (LDA). The experimental unit consists of machinery module for induction motor drive and data acquisition module to obtain the fault signal. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by mutual information As the next step, feature extraction is performed by LDA, and then diagnosis is evaluated by k-NN classifier. The results to verify the usability of the proposed algorithm showed better performance than various conventional methods.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.1
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• pp.30-41
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• 2023

With the aggressive down-scaling of advanced integrated circuits (ICs), electronic packages have become the bottleneck of both reliability and performance of whole electronic systems. In order to resolve the reliability issues, Institute of Electrical and Electronics Engineers (IEEE) laid down a roadmap on fault detection and diagnosis (FDD), thrusting the digital twin: a combination of reliability physics and artificial intelligence (AI). In this paper, we especially review research works regarding the signal-based FDD approaches on the electronic packages. We also discuss the research trend of FDD utilizing AI techniques.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.938-943
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• 2008

Coupling capacitor voltage transformers(CCVTs) have been used in extra or ultra high voltage systems to obtain the standard low voltage signal for protection and measurement. For fast suppression of the phenomenon of ferroresonance, three winding CCVTs are used instead of two winding CCVTs. A tuning reactor is connected between a capacitor voltage divider and a voltage transformer to reduce the phase angle difference between the primary and secondary voltages in the steady state. Slight distortion of the secondary voltage is generated when no fault occurs. However, when a fault occurs, the secondary voltage of the CCVT has significant errors due to the transient components such as dc offset component and/or high frequency components resulting from the fault. This paper proposes an algorithm for compensating the secondary voltage of a three winding CCVT in the time domain. With the values of the measured secondary voltage of the three winding CCVT, the secondary, tertiary and primary currents and voltages are estimated; then the voltages across the capacitor and the tuning reactor are calculated and then added to the measured voltage. Test results indicate that the algorithm can successfully compensate the distorted secondary voltage of the three winding CCVT irrespective of the fault distance, the fault impedance and the fault inception angle as well as in the steady state.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.1
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• pp.100-105
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• 2003

In this paper, we propose the novel test method effectively to detect short and open faults in CMOS op-amp. The proposed method uses a sinusoidal signal with higher frequency than unit gain bandwidth. Since the proposed test method doesn't need complex algorithm to generate test pattern, the time of test pattern generation is short, and test cost is reduced because a single test pattern is able to detect all target faults. To verify the proposed method, CMOS two-stage operational amplifier with short and open faults is designed and the simulation results of HSPICE for the circuit have shown that the proposed test method can detect short and open faults in CMOS op-amp.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.533-540
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• 2017

Distance relay identifies the type and location of fault by measuring the transmission line impedance. However any other factors that cause miss calculating the measured impedance, makes the relay detect the fault in incorrect location or do not detect the fault at all. One of the important factors which directly changes the measured impedance by the relay is series capacitive compensation (SCC). Another factor that changes the calculated impedance by distance relay is fault resistance. This paper provides a method based on the combination of distance and differential protection. At first, faulty transmission line is detected according to the current data of buses. After that the fault location is calculated using the proposed algorithm on the transmission line. This algorithm is based on active power calculation of the buses. Fault resistance is calculated from the active powers and its effect will be deducted from calculated impedance by the algorithm. This method measures the voltage across SCC by phasor measurement units (PMUs) and transmits them to the relay location via communication channels. The transmitted signals are utilized to modify the voltage signal which is measured by the relay. Different operating modes of SCC and as well as different faults such as phase-to-phase and phase-to-ground faults are examined by simulations.

• The KSFM Journal of Fluid Machinery
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• v.7 no.2 s.23
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• pp.41-49
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• 2004

Condition monitoring is very important in turbo machinery because single failure could cause critical damages to its plant. So, automatic fault recognition has been one of the main research topics in condition monitoring area. We have used a relatively new fault recognition method, Hidden Markov Model(HMM), for mechanical system. It has been widely used in speech recognition, however, its application to fault recognition of mechanical signal has been very limited despite its good potential. In this paper, discrete HMM(DHMM) was used to recognize the faults of rotor system to study its fault recognition ability. We set up a rotor kit under unbalance and oil whirl conditions and sampled vibration signals of two failure conditions. DHMMS of each failure condition were trained using sampled signals. Next, we changed the setup and the rotating speed of the rotor kit. We sampled vibration signals and each DHMM was applied to these sampled data. It was found that DHMMs trained by data of one rotating speed have shown good fault recognition ability in spite of lack of training data, but DHMMs trained by data of four different rotating speeds have shown better robustness.