• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.321-328
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• 1998

A controller and sensor fault tolerant system jot a steam generator is designed with fuzzy logic. A structure of the : proposed fault tolerant redundant system is composed of a supervisor and two fuzzy weighting modulators. A supervisor alternatively checks a controlled and a sensor induced performances to identify Which Part, a controller or a sensor, is faulty. In order to analyze controller induced performance both an error and a charge in error of the system output an chosen as fuzzy variables. The fuzzy logic jot a sensor induced performance uses two variables : a deviation between two sensor outputs and its frequency, Fuzzy weighting modulator generates an output signal compensated for faulty input signal. Simulations show that the : proposed fault tolerant control scheme jot a steam generator regulates welt water level by suppressing fault effect of either controllers or sensors. Therefore through duplicating sensors and controllers with the proposed fault tolerant scheme, both a reliability of a steam generator control and sensor system and that of a power plant increase even mote.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.498-504
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• 2015

This paper proposed an Spread Spectrum Time Domain Reflectometry (SSTDR) using time-frequency correlation analysis in order to have more accurate fault determination and location detection than classical SSTDR despite increased signal attenuation due to the long distance to cable fault location. The proposed method was validated through comparison with classical SSTDR methods in open- and short-circuit fault detection experiments of low-voltage power cables. The experimental results showed that the proposed method can detect correlation coefficients at fault locations accurately despite reflected signal attenuation so that cable faults can be detected more accurately and clearly in comparison to existing methods.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.95-98
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• 1995

In this paper, a good fault location algorithm will be presented, which uses novel signal processing techniques and takes a new paradigm to overcome some drawbacks of the conventional methods. The main feature of the method is that it uses the high frequency components in fault signal and considers the influence of the source network by using a traveling wave concept.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.15-19
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• 1994

The application of neural network for fault dection of cutting force in turning was introduced. This monitoring system consist of a RBF predicton model and a ART-1 pattern classifier. RBF prediction model predict a cutting force signal. Prediction error of predictor is used for a input vector of ART-1 pattern classifier. Prediction error could be successfully performed to fault signal monitoring of ART-1 pattern classifier.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.642-647
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• 2004

The relations of fuzzy entropy, distance measure, and similarity measure are discussed in this paper. For the purpose of reliable signal selection, the fuzzy entropy is proposed by a distance measure. Properness of the proposed entropy is verified by the definition of the entropy measure. Fourier and Wavelet transform are applied to the stator current signal to obtain the fault features of an induction motor. Membership functions for 3-phase currents are obtained by the Bootstrap method and Central Limit Theorem. Finally, the proposed entropy is applied to measure the fault signal of an induction machine, and the fuzzy entropy values of phase currents are illustrated.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1543-1544
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• 2008

In this paper, we introduce a gaussian enveloped linear chirp signal that can change parameters for consideration of target material characteristics. Using the gaussian enveloped linear chirp signal, time-frequency domain reflectomety is able to detect fault location in power transmission line. we suggest design method of reference signal for power transmission line fault detection. This method is verified by locating fault in HIV low voltage power transmission line.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.671-675
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• 2008

Railway signal system is responsible for the safety operation of railway and performs vital functions as safe space control, route control and etc. These functions prevent collision accidents between trains and derailment accidents of trains. However, these accidents are occurred by some causes. It is necessary to analysis hazards, hazard frequency and risk contribution. And railway signal system must make practical application of the analysis results. This paper includes analysis results of railway accident data by FTA(Fault Tree Analysis) and hazards. Railway signal system must consider these hazards. This paper used the railway accident data of RSSB(Railway Safety & Standard Board) of UK. We will use the FTA result to set up a draft of safety criteria of railway signal system.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.143-147
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• 2005

Monitoring and diagnosis of the operating machines are very important for safety operation and maintenance in the industrial fields. These machines are most rotating machines and the diagnosis of the machines has been researched for long time. We can easily see the faulted signal of the rotating machines from the changes of the signals in frequency. The Linear Predictive Coding(LPC) is introduced for signal analysis in frequency domain. In this paper, we propose fault detection and diagnosis method using the Linear Predictive Coding(LPC) and residual signal energy. We applied our method to the induction motors depending on various status of faulted condition and could obtain good results.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.1-13
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• 2020

In this paper, the author proposed a nuclear power plant (NPP) instrumentation signal faults identification algorithm. A variational autoencoder (VAE)-based model is trained by using only normal dataset as same as existing anomaly detection method, and trained model predicts which signal within the entire signal set is anomalous. Classification of anomalous signals is performed based on the reconstruction error for each kind of signal and partial derivatives of reconstruction error with respect to the specific part of an input. Simulation was conducted to acquire the data for the experiments. Through the experiments, it was identified that the proposed signal fault identification method can specify the anomalous signals within acceptable range of error.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.859-868
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• 2012

A new fault location algorithm based on stationary wavelet transform and its verification experiment results are described for HVDC submarine cables in this paper. For wavelet based fault location algorithm, firstly, 4th level approximation coefficients decomposed by wavelet transform function are superimposed by correlation, then the distance to the fault point is calculated by time delay between the first incident signal and the second reflected signal. For the verification of this algorithm, the real experiments based on various fault conditions and return types of fault current are performed at HVDC submarine cable test yard located in KEPCO(Korea Electric Power Corporation) Power Testing Center of South Korea. It proves that the fault location method proposed in this paper is very simple but very quick and accurate for HVDC submarine cable fault location.