• Journal of Magnetics
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• v.21 no.3
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• pp.413-420
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• 2016

The permanent magnet synchronous motor has high efficiency driving performance and high power density output characteristics compared with other motors. In addition, it has good regenerative operation characteristics during braking and deceleration driving condition. For this reason, permanent magnet synchronous motor is generally applied as a power train motor for electrical vehicle. In permanent magnet synchronous motor, the most probable causes of fault are demagnetization of rotor's permanent magnet and short of stator winding turn. Therefore, the demagnetization fault of permanent magnet and turn fault of stator winding should be detected quickly to reduce the risk of accident and to prevent the progress of breakdown of power train system. In this paper, the fault diagnosis method using high frequency low voltage injection was suggested to diagnose the demagnetization fault of rotor permanent magnet and the turn fault of stator winding. The proposed fault diagnosis method can be used to check the faults of permanent magnet synchronous motor during system check-up process at vehicle starting and idling stop mode. The feasibility and usefulness of the proposed method were verified by the finite element analysis.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.11
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• pp.109-115
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• 2012

Recently, permanent magnet synchronous motor are applied to various applications. Because of the importance of high reliable operation in these areas, many research related to the fault detection and diagnosis of inverter system are conducted. So, a faults model for an inverter-driven permanent magnet synchronous motor is studied by using the fault current of motor according to switch open, which can be effectively used for performance evaluation of the diagnostic algorithm. And fault of the permanent magnet synchronous motor inverter drive system is divided into four types. The feasibility of the proposed method are improved by simulation and experiment.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.438-445
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• 2004

This paper presents a new numerical spectral domain algorithm devoted to blocking unsuccessful automatic reclosing onto permanent faults and fault distance calculation. Arc voltage amplitude and fault distance are calculated from the fundamental and third harmonics of the terminal voltages and currents phasors. From the calculated arc voltage amplitude it can be concluded if the fault is transient arcing fault or permanent arcless fault. If the fault is permanent automatic reclosure should be blocked. The algorithm can be applied for adaptive autoreclosure, distance protection, and fault location. The results of algorithm testing through computer simulation and real field record are given.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.163-168
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• 2002

This paper present a new verb efficient numerical algorithm for arcing faults detection and fault distance estimation in transmission line. It is based on the fundamental differential equations describing the transients on a transmission line before, during and alter the fault occurrence, and on the application of the "Least Error Squares Technique"for the unknown model parameter estimation. If the arc voltage estimated is a near zero, the fault is without arc, in other words the fault is permanent fault. If the arc voltage estimated has any high value, the faust is identified as an fault, or the transient fault. In permanent faults case, fault distance estimation is necessary. This paper uses the model of the arcing fault in transmission line using ZnO arrestor and resistance to be implemented within EMTP. One purpose of this study is to build a structure for modeling of arcing fault detection and fault distance estimation algorithm using Matlab programming. In this paper, This algorithm has been designed in Graphic user interface(GUI).

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.416-424
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• 2016

In this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.1
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• pp.23-30
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• 2013

This paper proposes a parametric model for inter-turn fault detection in a fault-tolerant permanent-magnet (FTPM) machine, which can predict the effect of the short-circuit fault to various physical quantity of the machine. For different faulty operations, a new effective stator inter-turn fault detection method is proposed. Finally, simulations of vector-controlled FTPM machine drives are given to verify the feasibility of the proposed method, showing that even single-coil short-circuit fault could be exactly detected.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.79-81
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• 2003

This paper presents development and testing of a new numerical spectral domain algorithm devoted to blocking unsuccessful automatic reclosing onto permanent faults and the fault distance calculation. The arc voltage amplitude and the fault distance are calculated from the fundamental and third harmonics of the terminal voltages and currents phasors. From the calculated arc voltage amplitude it can be concluded if the fault is transient arcing fault or permanent arcless fault. If the fault is permanent automatic reclosure should be blocked. The algorithm can be applied for adaptive autoreclosure, distance protection, and fault location. The results of algorithm testing through computer simulation are given.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.9-17
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• 2010

Corrective control compensates the stable-state behavior of asynchronous sequential machines so that the closed-loop system can be changed in a desirable way. Using corrective control, we present a novel fault tolerance scheme that overcomes permanent faults for asynchronous sequential machines. When a permanent fault occurs to an asynchronous machine, the fault is not recovered forever while the machine is irreversibly stuck in a set of failure states. But, if the machine has control redundancy in the limited behavior range, corrective control can be applied to solve the fault tolerance problem against permanent faults. We present the condition on detecting permanent faults and the existence condition of an appropriate corrective controller. The design procedure for the proposed controller is described in a case study.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1347-1352
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• 2010

This paper presents a new adaptive single-phase auto reclosure (SPAR) algorithm to discriminate between a permanent fault and a transient fault and to minimize a protection dead time. The algorithm precisely detects the extinction of the secondary arc, based on THD's profiles on the faulted phase voltage waveform. The EMTP/ATPDraw program was used to simulate the single phase grounding fault for evaluating the proposed algorithm. And the simulation results show that the proposed algorithm is performing well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4774-4796
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• 2018

Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.