• Journal of Power Electronics
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• v.11 no.5
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• pp.759-766
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• 2011

This paper focuses on monitoring and predicting the short circuit faults of the rotor windings of large turbo-generator systems. For the purpose of increasing efficiency and decreasing maintenance cost, a method that combines the HHT (Hilbert Huang Transform) with a wavelet has been studied. This method is based on analyzing a classical Albright detecting coil. Due to the Empirical Mode Decomposition (EMD) and the Intrinsic Mode Functions (IMF) of the HHT the exact location of a short circuit of rotor windings may be given. However, a part of the useful information is eliminated by the unreasonable decomposing scale of the wavelet. Based on the thermodynamics modeling method, this study was illustrated with a 50MW turbo-generator system that is installed in Northern China. The analysis results, which have very good agreement with those of a previous study, show that the method of combining the HHT with a wavelet is an effective way to analyze and predict the short circuit faults of the rotor windings of large generators, such as supercritical turbo-generator systems and wind turbo-generator systems. This work can offer a useful reference for analyzing smart grids by improving the power quality of a distribution network that is supplied by a turbo-generator system.

• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.43.1-43.1
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• 2011

The detail simulation modeling of fully-fed induction generator is investigated through PC based MATLAB/Simulink environment. Generator's stator currents are controlled by indirect vector control method. In this method, generator side converter controls the maximum excitation (air gap flux) by stator d-axis current and controls generator torque by stator q-axis current. Induction generator speed is controlled by tip speed ratio (TSR) upon the wind speed variations in order to generate the maximum output power. The generator torque model is specified as a 3-blade wind turbine with rating, then, the model is simulated under normal operating condition and three different fault conditions. The matlab model designed for fully-fed induction generator based wind farm provides good performance under normal and grid fault conditions. It provides good results for different pwm techniques and fault conditions except the single-phase line to ground fault, which should be verified with real time data from wind farms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.6
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• pp.58-62
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• 2015

When an emergency generator is running, it supplies the power for critical loads. Generator protection requires the consideration of many abnormal conditions that may occur with generators include overvoltages and ground faults. Modern day power systems create harmonics within the electrical network that can have an impact upon the associated protective system. This paper focuses on the analysing of the cause and development of a solution for the malfunction of induction disc type overcurrent ground relay by generation of harmonics during emergency generator operation.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1234-1235
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• 2007

This paper represents the generating principles of the doubly-fed induction generator (DFIG) based wind power system and developes a simulation model of DFIG by using PSCAD/EMTDC. In addition, this paper analyzes the steady state operation and the transient operation during the voltage sags in the power common coupling. The voltage sags are occurred by three phase line-to-ground faults and full-voltage startup of an induction motor in the simulation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.7 s.337
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• pp.37-44
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• 2005

This paper presents effective test patterns and their BIST implementations for SoC and Board interconnects. Initially '6n'algorithm, where 'n' is the total number of interconnect nets, is introduced to completely detect and diagnose both static and crosstalk faults. Then, more economic 4n+1 algorithm is described to perfectly capture the crosstalk faults for the interconnect nets separated within a certain distance. It will be shown that both algorithms can be easily implemented as interconnect BIST hardwares with small area penalty than conventional LFSR.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• The Transactions of the Korea Information Processing Society
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• v.4 no.5
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• pp.1371-1379
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• 1997

Undetectable faults in a digital circuit are faults that no input patterms can detect.Identifying these faults in test geferation process is very time- consuming especially for sequential circuits .In this paper we present a new algorithm to identify unedtectable faults in sequential cirouits .In the alorithm. we identify uninitializable fip-flops and then, faults that prevent intialization of the fkip-flops(FPIs)are identified, finally propagation path of the FPI is checked. Time complexity of this algorithm is porportional to the product of the number of flip flops with at lest a self loop and the number of gates in the circuit. Experiments were performed on the ISCAS89 benchmark ciruits to show the feadibility of the proposed algorithm.We could identify large amount of undetectable faults(up to 50% of the number of flip-flops)in circuits with uninitializable flip-flops. Consider-ing that most of the time in test generation is cinsumed in identifying undetecatable faults, performance of test generator can be improved by using this algorithm as a pre-processing of test generation.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1724-1725
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• 2007

This paper presents a fault detection and isolation(FDI) scheme for a nonlinear systems with a actuator and sensor faults. A residual generator based on the observer model generate the information for a fault detection. The proposed fault estimators are activated for a fault isolation and applied to estimate the time-varying lumped faults(model uncertainty + fault). but a fault estimator error dose not converge to zero since the derivative of lumped fault is not zero. Then the fuzzy neural network(FNN) is used to estimate the fault estimator error. Simulation results are presented to illustrate the effectiveness and the applicability of the approaches proposed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1269-1275
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• 2015

Turbine-generator torsional response is caused by interaction between electrical transient air-gap torque and mechanical characteristics of turbine-generator shafts. There are various factors that affects torsional interaction such as fault, circuit breaker switching and generator mal-synchronizing, etc. Fortunately, we can easily simulate above torsional interaction phenomena by using ElectroMagnetic Transient Program (EMTP). However, conventional EMTP shows the incomplete response of super- synchronous torsional mode since it does not consider turbine blade section. Therefore, in this paper, we introduced mechanical-electrical analogy for detailed modeling of turbine-generator shaft system including low pressure turbine blade section. In addition, we derived the natural frequencies of modeled turbine-generator shaft system including turbine blade section and analyzed the characteristics of mechanical torque response at shaft coupling and turbine blade root area according to power system balanced/unbalanced faults.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.1
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• pp.35-40
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• 2015

Generators are the most complex and expensive single element in a power system. The generator protection relays should to minimize damage during fault states and must be designed for maximum reliability. A conventional CDR(Current Differential Relaying) technique based on DFT(Discrete Fourier Transform) filter have the disadvantages that the time information can lead to loss in the process of converting the signal from the time domain to the frequency domain. A WT(Wavelet transform) and WT analysis is known that it is possible with the local analysis of the fault and transient signal. In this paper, to overcome the defects in the DFT process, an application of WT for fault detection of generator is presented. This paper describes an selection of mother Wavelet to detect faults of generator. Using collected data from the fault simulation with ATPdraw, we analyzed the several mother Wavelet through the course of MLD(multi-level decomposition) using MATLAB software. Finally, it can be seen that the proposed technique using detail coefficient of Daubechies level 2 which can be fault discriminant of generator.