• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2627-2629
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• 2000

This paper introduces the design of a reduced order observer with unknown inputs for the purpose of fault detection and isolation(FDI) in a class of bilinear systems. To Analyze the observer and FDI, this paper uses BPF(block-pulse functions). The operational properties of BPF are much applied to the analysis of bilinear systems. The integral operational matrix BPF converts the form of the differential equation into the algebraic problems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.53-59
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• 2004

A calibration technique for a redundant IMU with low-grade inertial sensors is proposed. In order to calibrate the redundant IMU that can detect and isolate a faulty sensor, the fundamental coordinate frames in the IMU are defined and the IMU error is modeled based on the frames. Equations to estimate the error coefficients of the redundant IMU are formulated, and a test sequence using the 2-axis rate table is also presented. Finally, a redundant IMU with cone configuration is implemented using the low-grade inertial sensors and the performance of the proposed technique is verified by some experiments.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2295-2297
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• 2004

원자로의 제어봉 구동장치에 공급되는 전력을 제어하는 전력함 전력제어기는 DSP를 이용하여 디지털 시스템으로 설계하였다. 전력제어기는 Master/Slave 형태로 이중화되어 신뢰성이 향상시켰고 전력제어기의 CPU 보드에는 제어용과 통신용 두 개의 DSP를 사용하여 전력제어기의 주 기능인 제어/감시와 통신 기능을 분리하여 담당시켰다. 전력제어기에 요구되는 이러한 기능들을 효과적으로 수행하도록 CPU 보드에 디지털 논리구현 장치인 FPGA를 설치하여 메모리 주소 및 각 부품의 칩 선택 신호를 생성, 이중화 전력제어기 상호간 신호 수수, 각종 고장 검출 및 점호각 신호 발생 등의 역할을 하도록 하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1117-1124
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• 2011

An integrated fault detection and isolation method is proposed in this paper. The main objective of this paper is development fault detection, isolation and diagnosis algorithm based on the DKF (Decentralized Kalman Filter) and the bank of IMM (Interacting Multiple Model) filters using penalty scalar for both partial and total faults and the outlier detection algorithm for preventing false alarm also included. The proposed FDI (Fault Detection and Isolation) scheme is developed in four phases. In the first phase, the outlier detection filter is designed to prevent false alarm as a pre-filter. In the second phases, two local filters and master filter are designed to detect sensor faults. In the third phases, the proposed FDI scheme checks sensor residual to isolate sensor faults and 11 EKFs actuator fault models are designed to detect wherever actuator faults occur. In the last phases, four filters are designed to identify the fault type which is either the total fault or partial fault. The developed scheme can deal with not only sensor and actuator faults, but also preventing false alarm. An important feature of the proposed FDI scheme can decreases fault isolation time and figure out not only fault detection and isolation but also fault type identification. To verify the proposed FDI algorithm performance, the Simulator is also developed under the Matlab/Simulink environment.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.706-712
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• 2014

The inverters used to drive Brushless DC motors (BLDC) include switching devices such as FETs and the faults in FETs cause severe performance degradation in systems where a BLDC acts as actuator. This paper presents a fault detection and isolation method for the FETs of an inverter for BLDC motor control systems, which is based on the EKF (Extended Kalman filter). Firstly, an equivalent circuit model for a BLDC motor plus its inverter system was derived. Secondly, a state-space equation was established, where the on-resistance of the FETs is expressed as a state variable and the EKF equation estimates the on-resistance. If the estimated resistance differs greatly from the known value, it can be asserted that there is a fault on that FET. Thirdly, the local convergence of the established EKF was proved. Finally, through the experiments, the performance of the proposed method was verified. The results show that the on-resistance is estimated close to the value specified in the FET data sheet in normal operation, whereas the estimated resistance is a much larger value than the normal one in case an FET fault occurs. Therefore, it is confirmed that the proposed fault detection and isolation method works appropriately in real systems.