• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1847-1853
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• 2008

This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis to demonstrate convergence property of the proposed estimation by using statistical convergence and system stability theory. We apply our fault diagnosis approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.296-298
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• 2008

Currently SCADA System faces various fault situation. Operator must recognize all fault state and management plans. But it is not easy to recognize all category and acquired error data. So it is needed that automatic fault estimation. Automatic fault estimation is possible to data flow control. Data flow control method is two type. One is alarm processing and the other one is topology processing. This paper provide two type processing method in SCADA data flow control.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.257-262
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• 1999

This paper proposes a composite fault detection and isolation method by combining the parameter estimation method[1] with the observer-based method[2] to take advantages of both methods. Some properties of the parameter estimation method and the observer-based method are revieved, and the composite algorithm is presented. To exemplify the performance of the method proposed, some simulations applied to remotely piloted vehicle are performed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.2
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• pp.16-22
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• 2011

It is recognized that the control surface fault is detected by monitoring the value of the coefficients due to the control surface deviation. It is found out the control surface stuck position by comparing the trim value with the reference value. To detect and isolate the fault, two mixed methods apply to the real-time parameter estimation and similarity measure. If the scatter of aerodynamic coefficients for the fault and normal are closing nearly, fault decision is difficult. Applying similarity measure to decide for fault or not, it makes a clear and easy distinction between fault and normal. Low power processor is applied to the real-time parameter estimator and computation of similarity measure.

• Journal of Power Electronics
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• v.6 no.1
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• pp.8-17
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• 2006

In this paper, we propose a fault-tolerant control system for the position control and vibration suppression of a flexible arm robot. The proposed control system has a strain gauge sensor signal observer based on a reaction force observer and detects a fault by monitoring an estimated error. In order to improve the estimation accuracy, the plant parameters included in the sensor signal observer are updated by using the strain gauge sensor signal in normal time through the adaptive law. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We confirmed the effectiveness of the proposed control system through several experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.885-890
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• 2009

A fault location algorithm using estimated local source impedance after a fault is proposed in this paper. The method uses after fault data only at the local end. It uses the negative sequence current distribution factor for more accurate estimation. The proposed algorithm can keep up with the variation of the local source impedance. Therefore, the proposed algorithm especially is valid for a transmission line interconnected to a wind farm that the equivalent source impedance changes continuously. The performance of the proposed algorithm was verified under various fault conditions using the Simpowersystem of MATLAB Simulink. The proposed algorithm is largely insensitive to the variation in fault distance and fault resistance. The test results show a very high accurate performance.

• Journal of Power Electronics
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• v.13 no.6
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• pp.985-990
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• 2013

This paper proposes a novel fault diagnosis scheme using parameter estimation of the stator resistance, especially in the case of the open-phase faults of PMSM drives. The stator resistance of PMSMs can be estimated by the recursive least square (RLS) algorithm in real time. Fault diagnosis is achieved by analyzing the estimated stator resistance of each phase according to the fault condition. The proposed fault diagnosis scheme is implemented without any extra devices. Moreover, the estimated parameter information can be used to improve the control performance. The feasibility of the proposed fault diagnosis scheme is verified by simulation and experimental results.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.500-504
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• 2007

In this paper, the induction motor rotor fault diagnosis system using current signals, which are measured using axis-transformation method, and speed, which is estimated using current information, are presented. In inverter-fed motor drives unlike line-driven motor drives the stator currents have numerous harmonics components and therefore fault diagnosis using stator currents is very difficult. The current and speed signal for rotor fault diagnosis needs to be precise. Also, high resolution information, which means the diagnosis system, demands additional hardware such as low pass filter, high resolution ADC, encoder and etc. Therefore, the proposed axis-transformation and speed estimation method are expected to contribute to low cost fault diagnosis systems in inverter-fed motor drives without the need for an encoder and any additional hardware. In order to confirm validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation using Park transformation and speed estimation method are compared with the results obtained from fast Fourier transforms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2139-2146
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• 2008

This paper presents a numerical algorithm for fault location estimation which used to data from both end of the transmission line. The proposed algorithm is also based on the synchronized voltage and current phasor measured from the PMUs(Phasor Measurement Units) in the time-domain. This paper has separated from two part of with/without shunt capacitance(short/long distance). Most fault was arc one-ground fault which is 75% over [1]. so most study focused with it. In this paper, the numerical algorithm has calculated to distance for ground fault and line-line fault. In this paper, the algorithm is given with/without shunt capacitance using II parameter line model, simple impedance model and estimated using DFT(Discrete Fourier Transform) and the LES(Least Error Squares Method). To verify the validity of the proposed algorithm, the EMTP(Electro- Magnetic Transient Program) and MATLAB did used.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.244-251
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• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.