• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.6
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• pp.52-60
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• 2003

In aviation navigation using GPS, requirements on availability and integrity must be absolutely satisfied. Current study on accomplishing this integrity includes RAIM(Receiver Autonomous Integrity Monitoring), monitoring integrity internaIly in GPS receiver itself. Parity space technique as one of RAIM techniques has shown the advantages in fault detection and isolation due to each use of its magnitude and direction under the assumption of one fault. ln case of multiple fault, as biases in errors interact decreasing the effect of multiple fault in parity space, the exact fault detection and identification(FDI) may be difficult to be conducted. This paper focuses on FDI study on two faults and explains why parity space techniques applied on single fault is not adequate to the application of multiple fault case and shows that extended parity space technique may improve the performance of RAIM on two faults.

• 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.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1529-1543
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• 2005

Recently an unmanned aerial vehicle (UAV) has been widely used for military and civil applications. The role of a navigation system in the UAV is to provide navigation data to the flight control computer (FCC) for guidance and control. Since performance of the FCC is highly reliant on the navigation data, a fault in the navigation system may lead to a disastrous failure of the whole UAV. Therefore, the navigation system should possess a fault detection and isolation (FDI) algorithm. This paper proposes an attitude determination GPS/INS integrated navigation system with an FDI algorithm for a UAV. Hardware for the proposed navigation system has been developed. The developed hardware comprises a commercial inertial measurement unit (IMU) and the integrated navigation package (INP) which includes an attitude determination GPS (ADGPS) receiver and a navigation computer unit (NCU). The navigation algorithm was implemented in a real-time operating system with a multi-tasking structure. To evaluate performance of the proposed navigation system, a flight test has been performed using a small aircraft. The test results show that the proposed navigation system can give accurate navigation results even in a high dynamic environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.89-95
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• 2003

We consider a problem of application of analytical redundancy to engine synchronization process of spark ignition engines, which is critical to timing for every ECU process including ignition and injection. The engine synchronization process we consider here is performed using the pulse signal obtained by the revolution of crankshaft trigger wheel (CTW) coupled to crank shaft. We propose a discrete-time linear model for the signal, for which we construct FDI (Fault Detection & Isolation) system consisting residual generator and threshold based on linear observer.

• 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.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.97-110
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• 2012

High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.5-116
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• 2001

When inertial navigation system(INS) employ more sensors that mutually orthogonal sets to three, the redundant sensor system can have improved reliability and accuracy. For the redundant system the placement of redundant sensors is related to the system performance and also the number and proper orientation of sensors are important. We consider INS sensor configurations using two IMUs comprised mutually orthogonal sets of three. We suggest several configurations using two IMUs and analyze the system performance and the FDI(fault detection and isolation) properties from suggested configurations.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.4-116
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• 2001

We consider a robust configuration problem of inertial sensors for inertial navigation system(INS). Fault detection and isolation(FDI) is necessary to improve reliability of the system. For FDI, there used to be more than three mutually orthogonal sensors and thus we have to consider configuration methods of sensors. Various studies in this area have been done, but the former results did not consider effect of uncertainty(misalignment, scale factor error) to determine the configuration of the sensors. In this paper robust configuration of sensors is proposed through sensitivity analysis. Also total least square(TLS) method ...

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.673-681
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• 2005

As it is the most important to make sure security and reliability for nuclear Power Plant, it's considered the most crucial issues to develop a fault detective and diagnostic system in spite of multiple hardware redundancy in itself. To develop an algorithm for a fault diagnosis in the nuclear PWR steam generator, this paper proposes a method based on ART2(adaptive resonance theory 2) neural network that senses and classifies troubles occurred in the system. The fault diagnosis system consists of fault detective part to sense occurred troubles, parameter estimation part to identify changed system parameters and fault classification part to understand types of troubles occurred. The fault classification part Is composed of a fault classifier that uses ART2 neural network. The Performance of the proposed fault diagnosis a18orithm was corroborated by applying in the steam generator.