• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.825-833
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• 2020

Currently, the K-Water uses various valves that can be remotely controlled for optimal water management. Valve system fault can be classified into rotor defects, stator defects, bearing defects, and gear defects of induction motors. If the valve cannot be operated due to a gear fault, the water management operation can be greatly affected. For effective water management, there is an urgent need for preemptive repairs to determine whether gear is damaged through failure prediction diagnosis.. Recently, deep learning algorithms are being applied for valve failure diagnosis. However, the method currently applied has a disadvantage of attaching a vibration sensor to the valve. In this paper, propose a new algorithm to determine whether a fault exists using a convolutional neural network (CNN) based on the voltage and current information of the valve without additional sensor mounting. In particular, a normalized Lisasjous diagram was used to maximize the fault classification performance in the CNN-based diagnostic system.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.465-473
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• 2015

The increasing need to improve transient security assessment of existing or forecasted operating conditions of networks by power system operators is major concern of the power system security monitoring problem at the Energy Management Systems. This paper proposes a preventive control of transient stability with generation rescheduling based on rotor trajectory index obtained using time domain simulations. This index may help power engineers in making operational decision and to obtain a generation configuration with better transient security dispatch. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus New England system for a three phase fault at different loading conditions with single and multiple line outage cases.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.849-857
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• 2018

This paper aims is to study the effect of photovoltaic generation penetration and STATCOM on the transient stability of a single machine infinite bus (SMIB) system based on the rotor angle stability. The influence of STATCOM and PV penetration can be seen through damping oscillations, so that the generator remains stable with the rest of the system for various fault conditions. The simulation results obtained make it possible to efficient identify harmful and beneficial impact of increasing the PV penetration and the existence of STATCOM capability. The system model is created in MATLAB/ SIMULINK software.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.801-803
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• 2003

Faults in induction motors can be categorized into mechanical faults and electrical faults, and most mechanical faults result from inferiority or damage of the bearing, while most electrical faults derive from insulation faults of stator windings and rotor bar cracks. When a crack appears on the rotor bar, its efficiency decreases, which increases energy consumption and temperature, reducing the life span of the motor. This kind of fault can only be sensed by the protection relay after the condition has worsened to a certain degree, bringing massive economic loss. This paper will deal with the diagnosis method of rotor bar faults through the load current analysis method of the motor used during operation.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2011-2013
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• 2003

The effects of sensor faults on motor variables and control performance in induction motor drives are analyzed by both theoretical approach and simulation study, Vector control and direct torque control method for induction motor are well known. To control speed or position, the informations on rotor speed and rotor or stator flux are required in these control algorithms. The speed is measured by encoder. and the rotor or stator flux is estimated using motor parameters and measured currents. The control input generated based on the information from a faulted sensor should be far from the desired value and deteriorates the overall control performance.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.938-944
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• 2013

In this paper, we propose a method for suppressing shaft voltage by modifying the shape of the rotor and the permanent magnets in interior permanent magnet-type-high-voltage motors. Shaft voltage, which is induced by parasitic components and the leakage flux in motor-driven systems, adversely affects their bearings. In order to minimize shaft voltage, we designed a magnet rearrangement and rotor re-structuring of the motor. The shaft voltage suppression effect of the designed model was confirmed experimentally and by comparative finite element analysis.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.1-13
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• 2020

This paper presents an emergency brushless synchronous generator having rotating exciter status monitoring and protection functions. For monitoring the rotating exciter status, a wireless rotor status detector and a digital AVR(Automatic Voltage Regulator), which has a wireless communication capability, are proposed. The proposed rotor status detector detects temperatures of exciter armature and main field windings and input voltage and current of the main field. Therefore, it is possible to protect the generator from the over-temperature of windings and detect the exciter bridge diode fault. Furthermore, the proposed digital AVR has rotor status monitoring and protection function, and remote generator tuning, wireless group parallel operation function. So the operator can efficiently operate the generator using a smartphone from a remote area.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.813-814
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• 2013

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.809-810
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• 2013

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.874-882
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• 2003

The condition assessment of engineering systems has increased in importance because the manpower needed to operate and supervise various plants has been reduced. Especially, induction motors are at the core of most engineering processes, and there is an indispensable need to monitor their health and performance. So detection and diagnosis of motor faults is a base to improve efficiency of the industrial plant. In this paper, a model-based fault detection system is developed for induction motors, using steady state vibration signals. Early various fault detection systems using vibration signals are a trivial method and those methods are prone to have missed fault or false alarms. The suggested motor fault detection system was developed using a model-based reference value. The stationary signal had been extracted from the non-stationary signal using a data segmentation method. The signal processing method applied in this research is FFT. A reference model with spectra signal is developed and then the residuals of the vibration signal are generated. The ratio of RMS values of vibration residuals is proposed as a fault indicator for detecting faults. The developed fault detection system is tested on 800 hp motor and it is shown to be effective for detecting faults in the air-gap eccentricities and broken rotor bars. The suggested system is shown to be effective for reducing missed faults and false alarms. Moreover, the suggested system has advantages in the automation of fault detection algorithms in a random signal system, and the reference model is not complicated.