• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.808-810
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• 1996

In this paper, neural network, which has learning capability, is used for fault type classification and fault section estimation for high speed relaying. The potential of the neural network approach is demonstrated by simulation using ATP. The instantaneous values of voltages and currents are used the inputs of neural networks. This approach determines the fault section directly. In this paper, back-propagation network(BPN) is used for fault type classification and fault section estimation and can use for high speed relaying because it determines fault section within a few msec.

• 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.

• 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 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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.710-713
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• 2005

In this paper, a design method to detect faults in plants with uncertainties is proposed. When a plant has faults, the plant will be corrupted by an unknown fault signal. In addition, the plant also includes uncertainties, such as disturbances and plant parameter deviations. In this case, the proposed method estimates the fault signal by using an adaptive observer. Numerical examples are given to demonstrate the validity of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1552-1564
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• 1995

A fault detecting method of ternary logic is proposed by using the spectral coefficients of the Chrestenson function. Fault detecting conditions are derived for a stuck-at fault in case of single input, multiple inputs and internal lines in the ternary logic. The detecting conditions for min/max bridging faults are also considered. When using this fault analysis method, it is possible to detect faults without the test vector and minimize high volume memory for storing the vector and response data. Thus, the computational complexity for the test vector can be decreased.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.695-702
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• 1998

In this paper, we propose a novel fault isolation filter design method using the left eigenstructure assignment scheme proposed by Choi et. al., The proposed filter shows good fault isolation performance with exact eigenstructure assignment. An eigenstructure assignment methodology which satisfies the required fault isolation conditions is also proposed. The proposed method guarantees that the corrupted m simultaneous faults can be isolated when the number of available output measurements are (m+1).

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.12
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• pp.1073-1077
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• 2009

The iron core, which comprises the superconducting fault current limiter (SFCL) using magnetic coupling of coils, can be operated in the saturation region, especially at the initial fault period. This operation of the iron core in the saturation region deteriorates the fault current limiting operation of the SFCL. To solve the saturation problem of the SFCL using magnetic coupling of coils, the iron core with two magnetic paths, which has an air-gap in one of them, was adopted. In this paper, the hysteresis characteristics of SFCL using magnetic coupling of coils, which were wound in the iron core with two magnetic paths, were analyzed. Through comparative analysis on the hysteresis characteristics of the iron core comprising SFCL, the hysteresis characteristics of the iron core with two magnetic paths were confirmed to be kept in the non-saturation region during the fault period and thus, the effective fault current limiting operation of the SFCL using the magnetic coupling of coils could be performed.

• Journal of Power Electronics
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• v.9 no.2
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• pp.224-231
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• 2009

The induction motor rotor fault diagnosis system using current signals, which are measured using an axis-transformation method, is presented in this paper. In inverter-fed motor drives, unlike line-driven motor drives, the stator currents are rich in harmonics; therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which means the diagnosis system demands additional hardware such as a low pass filter, high resolution ADC, and encoder, etc. The proposed axis-transformation method with encoder and without encoder is expected to contribute to a low cost fault diagnosis system in inverter-fed motor drives without the need for any additional hardware. In order to confirm the validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation using Park transformation is compared with the results obtained from fast Fourier transforms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1774-1779
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• 2016

This paper proposes a portable cable fault detection system with automatic fault distinction and distance measurement using time-frequency correlation and reference signal elimination method and automatic fault classification algorithm in order to have more accurate fault determination and location detection than conventional time domain refelectometry (TDR) system despite increased signal attenuation due to the long distance to cable fault location. The performance of the developed system method was validated via an experiment in the test field constructed for the standardized performance test of power cable fault location equipments. The performance evaluation showed that accuracy of the developed system is less than 1.34%. Also, an error of automatic fault type and location by detection of phase and peak value through elimination of the reference signal and normalization of correlation coefficient and automatic fault classification algorithm not occurred.