• 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.

• 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.

• 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.

• Aerospace Engineering and Technology
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• v.3 no.1
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• pp.179-187
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• 2004

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method which solves the problems of the Modified SPRT method. The problems of the Modified SPRT method to apply to inertial sensor system come from the effect of inertial sensor errors and the correlation of parity vector components. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which reduces the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled party vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• Journal of Applied Reliability
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• v.12 no.2
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• pp.105-119
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• 2012

In this paper, we have proposed a methodology which can make effective test for system integration of complex guided missile system. System integration test play a significant role in the development of weapon system, providing the means to detect and isolate faults on first linkage between sub-systems. Integration tests for domestic weapon system has executed not a technology-intensive method based on tool but labor-intensive method based on experience. Higher cost, longer period, and more resource are required to execute system integration test for complex guided missile system comparing with past weapon systems, because recently weapon systems have more complex and more networked functions. Because the proposed design method for system integration test decreases number of test case, it lead to a decrease of cost, period, and resource for integration test of weapon system. The proposed configuration for system integration test will ensure reliability through detection and isolation of fault on linkage between sub-systems.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1423-1427
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• 1997

This paper deals with an algebraic approach to FDI observer design procedure. In general, FDI observer can be designed a sLuenbrger-type and equations for unknown input and actuator fault estimation include derivation of system outputs which is not available from the measurement directly. At this point, this paper presents STWS approach which can convert the derivation procedure to the recursive algebraic form by using its orthogonality and disjointess to alleviate such problems.

• 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.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.11
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• pp.943-951
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• 2015

Inertial sensors are important components of navigation system whose performance and reliability can be improved by specific sensor arrangement configuration. For the reliability of the system, Fault Detection and Isolation (FDI) is conducted by comparing each signal of arranged sensors and many arrangement configuration were suggested to optimize FDI performance of the system. In this paper, multiple conic configuration is suggested with optimal navigation condition and its FDI performance is analyzed by established Figure Of Merit (FOM) under the condition for navigation optimality. From FOM comparison, the multiple conic configuration is superior to former one in point of FDI.

• Smart Structures and Systems
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• v.4 no.6
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• pp.779-794
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• 2008

Observer-based fault detection and isolation (FDI) filter design method is a model-based method. By carefully choosing the observer gain, the residual outputs can be projected onto different independent subspaces. Each subspace corresponds to the monitored structural element so that the projected residual will be nonzero when the associated structural element is damaged and zero when there is no damage. The key point of detection filter design is how to find an appropriate observer gain. This problem can be interpreted in a geometric framework and is found to be equivalent to the problem of finding a decentralized static output feedback gain. But, it is still a challenging task to find the decentralized controller by either analytical or numerical methods because its solution set is, generally, non-convex. In this paper, the concept of detection filter and iterative LMI technique for decentralized controller design are combined to develop an algorithm to compute the observer gain. It can be used to monitor structural element state: healthy or damaged. The simulation results show that the developed method can successfully identify structural damages.