• International Journal of Control, Automation, and Systems
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• 제6권3호
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• pp.339-350
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• 2008

A general active fault-tolerant control framework is proposed for nonlinear systems with sensor faults. According to their identifiability, all sensor faults are divided into two classes: identifiable faults and non-identifiable faults. In the healthy case, the control objective is such that all outputs converge to their given set-points. A fault detection and isolation module is firstly built, which can produce an alarm when there is a fault in the system and also tell us which sensor has a fault. If the fault is identifiable, the control objective remains the same as in the healthy case; while if the fault is non-identifiable, the control objective degenerates to be such that only the healthy outputs converge to the set-points. A numerical example is given to illustrate the effectiveness and feasibility of the proposed method and encouraging results have been obtained.

• 한국지능시스템학회논문지
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• 제14권7호
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• pp.830-837
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• 2004

본 논문에서는 비선형시스템에서 발생한 고장을 감지하고 분류하기 위한 신경회로망기반 고장진단 방법을 제안한다. 제안한 알고리듬에서는 시스템의 출력과 다층신경회로망 공칭모델 출력 사이의 오차가 미리 설정한 문턱값을 넘으면 고장을 감지한다. 고장이 감지되면 다층신경회로망과 ART2 신경회로망을 이용한 고장분류기에서 시스템에서 발생한 고장을 분류한다. 컴퓨터 시뮬레이션 결과로부터 제안한 고장진단방법이 비선형시스템에서의 고장감지 및 분류문제에 잘 적용됨을 알 수 있다.

• Smart Structures and Systems
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• 제17권6호
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2335-2339
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• 2003

To prevent the critical situation due to the fault in the aircraft sensor system, the fault tolerant system with triple or quadruple redundancy can be made. However, if the faults are occurred in two or more than sensors simultaneously, the conventional fault detection process, such as cross-channel monitoring, may give the wrong fault alarm. For this case, we can detect the fault by estimating the state vector based on the system dynamics model, which is nonlinear for aircraft. In this paper, we propose the unscented Kalman filter to estimate the nonlinear state vector. This filter utilizes the so-called unscented transformation of sigma points featured the statistical characteristics of the random variable. For verification, we perform the simulations for F-16 aircraft with accelerometers, gyros, GPS and air data system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.125.4-125
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• 2001

The problem of recongurable ight control is investigated, focusing on model reference adaptive control(MRAC) through imprecise fault diagnosis. The method integrates the fault detection and isolation(FDI) scheme with the model reference adaptive control, and can be implemented on-line and in real-time. The algorithm can cope with the fast varying parameters. The Simulation results demonstrate the ability of reconguration to maintain the stability and acceptable performance after a failure.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1239-1243
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• 2005

A multipath mitigation method using the fault detection and isolation technique is proposed for the CDGPS. The base station is assumed to be immune to the effect of the multipath. With this reasonable assumption, the effect of multipath in moving station is mitigated. For that, the double difference measurement is produced, and then another additional difference between code pseudorange and acclumulated carrier phase is calculated. The test statistic is constituted with those differences. The hypothesis testing is applied to that test statistic. The proposed test statistic makes use of the effect of multipath in code pseudoranges and it does not use time differences. Therefore the detection ability for multipath is improved in most environments. However, the increased number of differences makes the measurement noises larger. The performance of the method is compared with that of the conventional parity space method with code pseudorange.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.127.1-127
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• 2001

In this paper we propose an input/output model based fault diagnosis method to detect and isolate single faults in the robot arm control system. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation, When a change in the system occurs, the errors between the system output and the estimated output cross a predetermined threshold, and once a fault in the system is detected, and in this zone the estimated parameters are transferred to the fault classifier by ART2(adaptive resonance theory 2) neural network for fault isolation. Since ART2 neural network is an unsupervised neural network fault classifier does not require the knowledge of all possible faults to isolate the faults occurred in the system. Simulations are carried out to evaluate the performance of the proposed ...

• 제어로봇시스템학회논문지
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• 제10권1호
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• pp.1-9
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• 2004

Inertial navigation system with hardware redundancy must use FDI(Fault Detection and Isolation) method to remove the influence of faulty sensors. Until now, several FDI methods such as PSA(Parity Space Approach), GLT(Generalized Likelihood ratio Test) and OPT(Optimal Parity vector Test) method are generally used. However, because these FDI methods only consider the situation that the system has one faulty sensor, these methods cannot be directly adapted for the system with two faulty sensors. To solve this problem, in this paper, PSA method is analyzed and based on this result, new FDI method called EPSA is proposed to consider a detection and an isolation of two faulty sensors in inertial navigation system.

• 제어로봇시스템학회논문지
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• 제8권3호
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• pp.256-263
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• 2002

Optical Multistage Interconnection Networks(OMINs) comprising photonic switches have been studied extensively as important interconnecting building blocks for communication networks and parallel computing systems. A basic element of photonic switching networks is a 2$\times$2 directional coupler with two inputs and two outputs. This paper is concerned with the diagnosis of cross-talk-faults in OMINs. As the size of today's network becomes very large, the conventional diagnosis methods based on tests and simulation have become inefficient, or even more, impractical. In this paper, we propose a simple and easily implementable algorithm for detection and isolation of the single crosstalk-fault in OMINs. Specifically, we develope an algorithm fur the isolation of the source fault in switching elements whenever the single crosstalk-fault is detected in OMINS. The proposed algorithm is illustrated by an example of 16$\times$16 banyan network.

• 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.