• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.666-673
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• 1998

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square test and GLR(General likelihood ratio) test are applied for fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1489-1492
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• 1997

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square distribution is applied fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1401-1410
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• 2014

This paper presents a modified adaptive fading EKF (AFEKF) for sensor fault detection and isolation in the satellite. Also, the fault detection and isolation (FDI) scheme is developed in three phases. In the first phase, the AFEKF is modified to increase sensor fault detection performance. The sensor fault detection and sensor selection method are proposed. In the second phase, the IMM filer with scalar penalty is designed to detect wherever actuator faults occur. In the third phase of the FDI scheme, the sub-IMM filter is designed to identify the fault type which is either the total or partial fault. An important feature of the proposed FDI scheme can decrease the number of filters for detecting sensor fault. Also, the proposed scheme can classify fault detection and isolation as well as fault type identification.

• 전기학회논문지
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• 제63권3호
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• pp.376-382
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• 2014

E-Actuator is an essential part of an eVGT, it receives the command from the main ECU and controls the vane. An e-Actuator failure can cause an abrupt change in engine output and it may induce an accident. Therefore, it is required to detect anomalies in the e-Actuator in real time to prevent accidents. In this paper, an e-Actuator fault detection method using on-line parameter identification is proposed. To implement on-line fault detection algorithm, many constraints are considered. The test input and sampling rate are selected considering the constraints. And new recursive system identification algorithm is proposed which reduces the memory and MCU power dramatically. The relationship between the identified parameters and real elements such as gears, spring and motor are derived. The fault detection method using the relationship is proposed. The experiments with the real broken gears show the effectiveness of the proposed algorithm. It is expected that the real time fault detection is possible and it can improve the safety of eVGT system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.549-551
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• 1999

Recently, Several type of motors are used more widely in Fan system because of their low cost and high reliability. Therefore, the importance of fault detection and isolation of fan system significantly increases. The motor is a important factor bring out the fan system fault. So the problem of a fault detection for motor based on a parameter identification will be considered in this paper. After an introduction into fault detection with parameter estimation, a mathematical model for motor with special emphasis on motor itself. In the fault detection system, current and motor speed are used as parameter. Finally, simulation results are used to demonstrate the efficiency of the fault detection system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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• pp.199-200
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• 2008

Demand for reliability and safety in modem systems has been increased in the research on fault detection and isolation. At traditional approaches to fault detection, redundant sensors have been used. More advanced methods are the residual analysis of signals which are created by the comparison between the actual plant behavior and the output response of a mathematical model. However, mathematical system models are difficult to obtain by using physical laws. These problems can be solved by system identification. In this paper, the transfer function of a direct current motor is estimated by using the system identification. And, the efficiency of the fault detector design is verified by using experiments.

• 전기학회논문지P
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• 제66권1호
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• pp.27-32
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• 2017

This paper presents a Daubechies wavelet-based fault detection method for fault identification in transmission lines. After the Daubechies wavelet coefficients are calculated, the proposed algorithm has been implemented difference equation using C language. We have modeled a 154kV transmission line using the ATPDraw software and have acquired test data. In order to evaluate effects of DC offset, simulations carried out while varying an inception angle of the voltage $0^{\circ}$, $45^{\circ}$, $90^{\circ}$. For performance evaluation, fault distance was varied. As we can see from the off-line simulation, the proposed algorithm shows rapid and accurate fault detection. Also we can see the proposed algorithm is not affected by the fault inception angle change.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.

• 항공우주기술
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• 제6권2호
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• pp.21-28
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• 2007

본 논문의 목표는 고장허용제어시스템에 대한 기반 연구로서 무인비행기 안전성 향상을 위하여 조종면 작동불능과 같은 고장에 대해 검출 방법을 제시하는 것이다. 조종면 고장검출을 위한 실시간 시스템식별 알고리듬은 퓨리에 변환기법을 사용하였으며 프로그램 성능 및 검증을 위해 HILS 시험과 비행시험을 수행하였다. 엘리베이터 조종면 고장은 피칭모멘트에 대한 조종면 효과를 나타내는 조종미계수를 실시간 추정하여 정상상태의 값과 비교함으로써 검출된다. 비행시험 결과를 통해 고장상태의 조종미계수 값은 정상상태의 값보다 작다는 것을 확인하였다.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.928-934
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• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.