• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.329-336
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• 2007

This paper considers a fault accommodation problem for inertial navigation systems (INS) that have redundant inertial sensors such as gyroscopes and accelerometers. It is wellknown that the more sensors are used, the smaller the navigation error of INS is, which means that the error covariance of the position estimate becomes less. Thus, when it is decided that double faults occur in the inertial sensors due to fault detection and isolation (FDI), it is necessary to decide whether the faulty sensors should be excluded or not. A new accommodation rule for double faults is proposed based on the error covariance of triad-solution of redundant inertial sensors, which is related to the navigation accuracy of INS. The proposed accommodation rule provides decision rules to determine which sensors should be excluded among faulty sensors. Monte Carlo simulation is performed for dodecahedron configuration, in which case the proposed accommodation rule can be drawn in the decision space of the two-dimensional Cartesian coordinate system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.1
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• pp.44-49
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• 2003

This paper describes a percentage current differential relaying algorithm for bus protection blocked by a CT saturation detection algorithm. The detection algorithm blocks the output of a current differential relay only if a differential current is caused by CT saturation in the case of an external fault. Moreover, if a current differential relay operates faster than the detection algorithm, the blocking signal is not ignited. On the other hand. if the detection algorithm operates faster than a current differential relay, the output of the relay is blocked. The results of the simulation show that the proposed algorithm can discriminate internal faults from external faults ever when a CT is saturated in both cases. This paper concludes by implementing the algorithm into the TMS320C6701 digital signal processor. The results of hardware implementation are also satisfactory The algorithm can not only increase the sensitivity of the current differential relay but Improve the stability of the relay for an external faults.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.432-437
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• 2004

Since the characteristic frequency is decreased in proportion to the fault distance, the characteristic frequency component may be insufficiently eliminated by a low-pass filter on a long transmission line. In order to set a standard for the cut-off frequency of the low-pass filter, this paper proposes a method for obtaining the characteristic frequencies due to line faults. The application results of the proposed method are presented for line to ground (LG) faults and line to line (LL) faults on a 345 kV 200 km overhead transmission line. The EMTP is used to generate fault signals under different fault locations and fault inception angles. By comparison between the characteristic frequencies obtained from the proposed method and the EMTP simulation, it is shown that the proposed method accurately obtains the characteristic frequency.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.16-21
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• 1999

The analysis of distribution line faults is essential to the proper protections of the power system. A high impedance fault test, which was carried in Korean electric power systems, it was found that a arcing phenomenon occurred during the high level portion of conductor voltage in each cycle. In this paper, we propose a new method for detection of high impedance faults, which uses the arcing fault current difference during high voltage and low voltage portion of conductor voltage waveform. To extract this difference, we diveded one cycle fault current into equal spanned four data windows according to the magnitude of voltage waveform and applied fast fourier transform(FFT) to each data window. The frequency spectrum of current wavefrom in each portion are used as the inputs of neural network and is trained to detect high impedance faults. The proposed method shows improved accuracy when applied to staged fault data and fault-like load.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.417-420
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• 2003

In this paper, we have designed the ground faults detection and disconnection algorithm at normal rendition of AC 120V to 240V rating voltage. Ground faults in electrical network have the characteristics of low current, 60Hz frequency to 2kHz frequency. The load rendition are no load and 20A load. The controller have the trip level are 6mA with ground faults. Conventional controller does not have the miswiring condition. The Controller algorithm using pic16c71 microprotessor.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.742-749
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• 2011

Power transmission lines are one of the most important components of electric power system. Failures in the operation of power transmission lines can result in serious power system problems. Hence, fault diagnosis (transient or permanent) in power transmission lines is very important to ensure the reliable operation of the power system. A hidden Markov model (HMM), a powerful pattern recognizer, classifies events in a probabilistic manner based on fault signal waveform and characteristics. This paper presents application of HMM to classify faults in overhead power transmission lines. The algorithm uses voltage samples of one-fourth cycle from the inception of the fault. The simulation performed in EMTPWorks and MATLAB environments validates the fast response of the classifier, which provides fast and accurate protection scheme for power transmission lines.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.35-41
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• 2006

This paper presents a new numerical algorithm for fault location estimation and for faults recognition based on the synchronized phasors. The proposed algorithm is based on the synchronized phasor measured from the synchronized PMUs installed at two-terminals of the transmission lines. In order to discriminate the fault type, the arc voltage wave shape is modeled numerically on the basis of a great number of arc voltage records obtained by transient recorder. From the calculated arc voltage amplitude it can make a decision whether the fault is permanent or transient. The results of the proposed algorithm testing through computer simulation are given.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.205-207
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• 2009

In 2007, 9,128 fires are attributed to electrical equipments. These fires resulted in 29 deaths and 262 injuries. Arc-faults were one of the major causes of these fires. When an unintended arc-fault occurs, it generates intense heat that can easily ignite surrounding combustibles. Conventional circuit breakers only respond to overloads, short circuits, and leakage currents. Therefore, the breakers do not protect against arcing conditions. This paper presents results obtained in experiments on ignition behavior of wire by series arc fault currents and techniques developed to detect the arc-faults. The developed technique was tested after installation to make sure they are working properly and protecting the circuit. If the developed arc detecting technique is applied, the electrical fires caused by an arc-fault can be reduced.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.170-177
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• 2014

This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.822-826
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• 2013

In this paper, we propose an AFDO (Adaptive Fault Diagnosis Observer) and a fault tolerant controller for a class of nonlinear continuous-time system under the nonlinear abrupt actuator faults. Together with its estimation laws, the AFDO which estimates that the actuator faults is designed by using the Lyapunov analysis. Then, based on the designed AFDO, an adaptive sliding mode controller is proposed as the fault tolerant controller. Using Lyapunov stability analysis, we also prove the uniform boundedness of the state, the output and the fault estimation errors, and the asymptotic stability of the tracking error under the nonlinear time-varying faults. Finally, we illustrate the effectiveness of the proposed diagnosis method and the control scheme thorough computer simulations.