• 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.

• Smart Structures and Systems
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• v.29 no.6
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• pp.785-790
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• 2022

Condition monitoring of permanent magnet synchronous motors (PMSMs) and detecting faults such as eccentricity and demagnetization are essential for ensuring system reliability. Motor current signal analysis is the most commonly used precursor for detecting faults in the PMSM drive system. However, the current signature responds sensitively to the load and temperature of the motor, thereby making it difficult to monitor faults in real- applications. Therefore, in this study, a condition monitoring methodology that detects motor faults, including their classification with standstill conditions, is proposed. The objective is to detect and classify faults of PMSMs by using programmable inverter without additional sensors and systems for detection. Both DC and AC were applied through the d-axis of a three-phase motor, and the change in incremental inductance was investigated to detect and classify faults. Simulation with finite element analysis and experiments were performed on PMSMs in healthy conditions as well as with eccentricity and demagnetization faults. Based on the results obtained from experiments, the proposed method was confirmed to detect and classify types of faults, including their severity.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1614-1622
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• 2018

The research related to fault diagnosis in permanent magnet synchronous motors (PMSMs) has attracted considerable attention in recent years because various faults such as permanent magnet demagnetization and short-circuited turns can occur and result in unexpected failure of motor related system. Several conventional current and back electromotive force (BEMF) analysis techniques were proposed to detect certain faults in PMSMs; however, they generally deal with a single fault only. On the contrary, cases of multiple faults are common in PMSMs. We propose a fault diagnosis method for PMSMs with single and multiple combined faults. Our method uses three phase BEMF voltages based on the fast Fourier transform (FFT), support vector machine(SVM), and visualization tools for identifying fault types and severities in PMSMs. Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) are used to visualize the high-dimensional data into two-dimensional space. Experimental results show good visualization performance and high classification accuracy to identify fault types and severities for single and multiple faults in PMSMs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.568-574
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• 2017

This paper proposes a demagnetization fault diagnosis method for interior permanent magnet synchronous motors(IPMSMs). In particular, a demagnetization fault is one of the most frequent electrical faults in IPMSMs. This paper proposes an estimation method for permanent magnet flux. The method is based on linear interpolation. The effectiveness of the proposed method for diagnose demagnetization faults is verified through various operating conditions by finite element simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.394-401
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• 2017

Fault diagnosis is important due to the increasing demand of using interior permanent magnet synchronous machines (IPMSMs). In particular, an interturn fault is one of the most frequent electrical faults in IPMSMs. This paper proposes a fault indicator for diagnosis of interturn faults in IPMSMs. The fault indicator is developed by negative-sequence impedance. The effectiveness of the fault indicator to diagnose interturn faults was verified through various fault conditions.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.826_827
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• 2009

This paper introduces major potential faults of Poly-Phase Permanent Magnet Synchronous Motor and their simulation realization methods. The faults of Poly-Phase PM Synchronous Motor, generally, stator turn faults, demagnetizing field. Based on the derived expressions, Poly-Phase PM synchronous Motor simulation model, which is capable of representing stator turn faults, is implemented in Maxwell.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2326-2333
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• 2015

Stator turn faults in permanent magnet synchronous motors (PMSMs) are more dangerous than those in induction motors (IMs) because of the presence of spinning rotor magnets that can be turned off at will. Condition monitoring and fault detection and diagnosis of the PMSM have been receiving a growing amount of attention among scientists and engineers in the past few years. The aim of this study is to propose a new detection technique of stator winding faults in a three-phase PMSM. This technique is based on the image analysis and recognition of the stator current Concordia patterns, and will allow the identification of turn faults in the stator winding as well as its correspondent fault index severity. A test bench of a vector controlled PMSM motor behaviors under short circuited turn in two phases stator windings has been built. Some experimental results of the phase to phase short circuits have been performed for diagnosis purpose.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.8-15
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• 2006

Since the power swing depends on the operating time of the relay, the swing's magnitude can be reduced by an autoreclosure relaying system with an optimal reclosing algorithm. This paper proposes a method for stability improvement using optimal reclosure relaying. An optimal reclosure algorithm is applied to identify both temporary and permanent faults, and to predict system stability by applying WAM and high speed communication technology. It provides optimal control by predicting and determining the degree of stability, considering the real time transient stability using EEEAC. For temporary faults, the algorithm determines the system's stability and either recloses optimally for stable systems, or inserts series capacitance before optimal reclosure for unstable systems. It also applies an optimal reclosure algorithm to minimize shock and damage to the power system when reclosure fails due to permanent faults.

• Journal of Electrical Engineering and Technology
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• v.6 no.3
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• pp.356-363
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• 2011

Vibrations and noise in electrical machines are directly related to the characteristics of the radial forces on one hand, and mechanical behavior on the other [1, 4]. The characteristics of these forces depend on the air gap flux density, which is also influenced by other factors, such as stator slots and poles, saturation level, winding type, and certain faults. The aim of this work is to investigate the effect of eccentricity and demagnetization faults on electromagnetic noise generated by the external surface of Permanent Magnet Synchronous Machine [PMSM]. For this purpose, an analytical electromagnetic vibroacoustic model is developed. The results confirm the effect of eccentricity and demagnetization fault in generating some low modes radial forces.

• 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).