• Title/Summary/Keyword: Fault detection and isolation scheme

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Fault Diagnosis of Shunt Motor using Artificial Neural Network (인공 신경망을 이용한 분권 전동기의 고장 진단)

  • Lee, Kee-Sang;Choi, Nak-Won;Lim, Jea-Hyung;Lee, Jeong-Dong
    • Proceedings of the KIEE Conference
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    • 1994.07a
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    • pp.21-23
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    • 1994
  • A Fault Detection. Isolation scheme based on ANN(Artifical Neural Network) is proposed for the supervision of a DC shunt motor. The Proposed FDI scheme can promptly detect the occurence of fault and classify all the faults that may occur during the operation. Also. it covers the full operating range in spite that the mathematical model of the motor contain strong nonlinearities. The simulation results show that the FDIU has good diagnostic ability even in the noisy environment.

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Analysis of Sensor Fault Effect in Induction Motor Drives (유도전동기 드라이브 시스템에서 센서 고장효과 분석)

  • 이기상;류지수
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.5
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    • pp.126-133
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    • 2003
  • High performance induction motor drives are driven by two advanced control methods: vector control and direct torque control (DTC). In order to apply the control methods to the speed/position control systems, the informations on rotor speed and rotor or stator flux are required. The speed is measured by encoder, and the rotor or stator flux is estimated by using the motor parameters and measured currents. The control input generated on the basis of the information that is provided by abnormal sensors should be far from the desired value and deteriorates the overall control perfonnance. In this paper, the effects of sensor faults on the motor variables and the control performance of induction motor drives are analyzed by both theoretical approach and simulation study. The presented analysis results could be utilized for the purpose of developing a fault detection and isolation scheme in induction motor drives.

Attitude Estimation for Satellite Fault Tolerant System Using Federated Unscented Kalman Filter

  • Bae, Jong-Hee;Kim, You-Dan
    • International Journal of Aeronautical and Space Sciences
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    • v.11 no.2
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    • pp.80-86
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    • 2010
  • We propose a spacecraft attitude estimation algorithm using a federated unscented Kalman filter. For nonlinear spacecraft systems, the unscented Kalman filter provides better performance than the extended Kalman filter. Also, the decentralized scheme in the federated configuration makes a robust system because a sensor fault can be easily detected and isolated by the fault detection and isolation algorithm through a sensitivity factor. Using the proposed algorithm, the spacecraft can continuously perform a given mission despite navigation sensor faults. Numerical simulation is performed to verify the performance of the proposed attitude estimation algorithm.

ADAPTIVE FDI FOR AUTOMOTIVE ENGINE AIR PATH AND ROBUSTNESS ASSESSMENT UNDER CLOSED-LOOP CONTROL

  • Sangha, M.S.;Yu, D.L.;Gomm, J.B.
    • International Journal of Automotive Technology
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    • v.8 no.5
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    • pp.637-650
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    • 2007
  • A new on-line fault detection and isolation(FDI) scheme has been proposed for engines using an adaptive neural network classifier; this paper investigates the robustness of this scheme by evaluating in a wide range of operational modes. The neural classifier is made adaptive to cope with the significant parameter uncertainty, disturbances, and environmental changes. The developed scheme is capable of diagnosing faults in the on-line mode and can be directly implemented in an on-board diagnosis system(hardware). The robustness of the FDI for the closed-loop system with crankshaft speed feedback is investigated by testing it for a wide range of operational modes, including robustness against fixed and sinusoidal throttle angle inputs, change in load, change in an engine parameter, and all changes occurring simultaneously. The evaluations are performed using a mean value engine model(MVEM), which is a widely used benchmark model for engine control system and FDI system design. The simulation results confirm the robustness of the proposed method for various uncertainties and disturbances.

Identification of Fuzzy Dynamic Model for Fault Diagnosis of Nonlinear System (비선형계통 고장진단을 위한 온-라인 퍼지동적모델 식별)

  • 이종렬;배상욱;이기상;박귀태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.204-210
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    • 1998
  • This paper discusses an on-line fuzzy dynamic model(FDM) identification of nonlinear processes for the design of fuzzy model based fault detection and isolation(FDI). The dynamic behavior of a nonlinear process is represented by a fuzzy aggregation of a set of local linear models. The identification is divided into two procedures. The first is the off-line identification of membership function. The second is the on-line identification of the local linear models. Then, we propose a residual generation scheme based on the parameters of local linear models and show that the scheme can be used for the design of FDI

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Reconfigurable Flight Control System Design Using Sliding Mode Based Model Following Control Scheme

  • Cho, Dong-Hyun;Kim, Ki-Seok;Kim, You-Dan
    • International Journal of Aeronautical and Space Sciences
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    • v.4 no.1
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    • pp.1-8
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    • 2003
  • In this paper, a reconfigurable flight control system is designed by applying the sliding mode control scheme. The sliding mode control method is a nonlinear control method which has been widely used because of its merits such as robustness and flexibility. In the sliding mode controller design, the signum function is usually included, but it causes the undesirable chattering problem. The chattering phenomenon can be avoided by using the saturation function instead of signum function. However, the boundary layer of the sliding surface should be carefully treated because of the use of the saturation function. In contrast to the conventional approaches, the thickness of the boundary layer of our approach does not need to be small. The reachability to the boundary layer is guaranteed by the sliding mode controller. The fault detection and isolation process is operated based on a sliding mode observer. To evaluate the reconfiguration performance, a numerical simulation using six degree-of-freedom aircraft dynamics is performed.

Process and instrument faults detection based on steam generator model (증기발생기 모델을 이용한 계통 및 계측기 고장검출에 관한 연구)

  • Kim, Jung-Soo;Lyou, Joon;Na, Nan-Ju;Kwon, Kee-Choon
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.250-255
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    • 1993
  • In this paper, for detection and isolation of instrument and process faults related with steam generator(S/G) in nuclear power plant, two types of observers are designed based on the linearized dynamic model of S/G : a bank of Dedicated Observers (DOS) for instrument faults detection and a bank of Unknown Input Observers(UIO) for process faults detection. And then, they are combined to decide which one between the above two faults occurs. In principle, the failure in ith instrument(process) can be isolated by monitoring the error between the ith output and its estimation obtained from the ith DOS(UIO). It is shown via computer simulations that the present scheme is feasible in finding out the source of a fault.

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Parameter Identification of Nonlinear Systems using Hopfield Network (Hopfield 신경망에 의한 비선형 계통의 파라미터 추정)

  • Lee, Kee-Sang;Park, Tae-Geon;Ham, Jae-Hoon
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.710-713
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    • 1995
  • Hopfield networks have been applied to the problem of linear system identification. In this paper, Hopfield network based parameter identification scheme of non-linear dynamic systems is proposed. Simulation results demonstrate that Hopfield network can be used effectively for the identification of non-linear systems assuming that the system states and their time derivatives are available. Therefore, the proposed scheme can be applied in fault detection and isolation(FDI) and adaptive control of non-linear systems where the Hopfield networks perform on-line identification of system parameters.

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Design on Fult Diagnosis System based on Dynamic Fuzzy Model (동적포지모델기반 고장진단 시스템의 설계)

  • 배상욱
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.2
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    • pp.94-102
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    • 2000
  • This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the unknown nonlinear system, which can detect and isolate process faults continuously over all ranges of operating condition. The dynamic behavior of a nonlinear process is represented by a set of local linear models. The parameters of the DFM are identified by an on-line methods. The residual vector of the FDI system is consisted of the parameter deviations from nominal model and the set of grade of membership values indicating the operating condition of the nonlinear process. The detection and isolation of faults are performed via a neural network classifier that are learned the relationship between the residual vector and fault type. We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.

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Real-time FDI Schemes for AC Motor Control Systems (교류전동기 제어시스템을 위한 실시간 고장검출진단)

  • Park Tae-Geon;Ryu Ji-Su;Lee Kee-Sang
    • Proceedings of the KIPE Conference
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    • 2002.07a
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    • pp.77-81
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    • 2002
  • In many high performance engineering systems such as automated production system and transportation systems, AC-servo drives are employed as the most Important driving parts. And the faults of servo drives result in overall system performance deterioration or an unscheduled shutdown In critical situations. The real-time fault detection and isolation(FDI) scheme Is very useful to prevent them and to guarantee the desired reliability of the overall system. In this paper, the FDI schemes which can be applied to AC servo drives are introduced and some new results are presented.

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