• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.200-206
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• 2005

In this paper, a redundancy management system for aircraft is studied, and FDI (Fault Detection and Isolation) algorithm of inertial sensor system is proposed. UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional FDI method cannot isolate multiple faults in a triple redundancy system. In this paper, hardware based FDI technique is proposed, which combines a parity equation approach with the wavelet based technique, which is a model-free FDI method. To verify the effectiveness of the proposed FDI method, numerical simulations are performed.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.313-323
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• 2014

Sensor fault detection and isolation problems subject to H_/$H_{\infty}$, performance are concerned for linear time-invariant systems with time delay in a state and parametric uncertainties. To that end, a model-based observer bank approach is pursued. The design conditions for both continuous- and discrete-time cases are formulated in terms of matrix inequalities, which are then converted to the problems solvable via an algorithm involving convex optimization.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.315-340
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• 2012

There are many types of seismic isolation devices that are being used today for structural control of earthquake response in buildings. The most commonly used are sliding bearings and elastomeric bearings, the latter with or without lead core. An alternative solution is the use of steel springs combined with viscoelastic fluid dampers, which is the case discussed in this paper. An analytical study of a three-story building supported on helical steel springs and viscoelastic fluid dampers, GERB Control System (GCS), subjected to near-fault earthquakes is presented. Several earthquakes records have been obtained by the acceleration network installed in the isolated building and in its non-isolated twin since they were finished. These experimental results are analysed and discussed. The aim is to show that the spring-based system can be an alternative for base isolation of small building located near active faults.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.115-118
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• 2001

In this paper we propose an FDI(fault detection and isolation) algorithm using neural network-based multi-fault models to detect and isolate single faults in nonlinear systems. When a change in the system occurs, the errors between the system output and the neural network nominal system output cross a threshold, and once a fault in the system is detected, the fault classifier statistically isolates the fault by using the error between each neural network-based fault model output and the system output.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.407-414
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• 2007

A sensor fault detection scheme(SFDS) for a class of nonlinear systems that can be represented by Takagi-Sugeno fuzzy model is proposed. Basically, the SFDS may be considered as a multiple observer scheme(MOS) in which the bank of state observers and the detection & isolation logic are included. However, the proposed scheme has two great differences from the conventional MOSs. First, the proposed scheme includes fuzzy fault detection observers(FFDO) that are constructed based on the T-S fuzzy model that provides very good approximation to nonlinear dynamic systems. Secondly, unlike the conventional MOS, the FFDOS are driven not parallelly but sequentially according to the predetermined sequence to avoid the massive computational burden, which is known to be the biggest obstacle to the practical application of the multiple observer based FDI schemes. During the operating time, each FFDO generates the residuals carrying the information of a specified fault, and the corresponding fault detection logic unit performs the logical operations to detect and isolate the fault of interest. The proposed scheme is applied to an inverted pendulum control system for sensor fault detection/isolation. Simulation study shows the practical feasibility of the proposed scheme.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.56-66
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• 2016

Robustness is essential for model based FDI (Fault Detection and Isolation) and it is inevitable to have modeling errors and sensor signal noises during the process of FDI. This study suggests an improved method by applying NARX (Nonlinear Auto Regressive eXogenous) model and Kalman estimator in order to cope with problems caused by linear model errors and sensor signal noises in the process of fault diagnoses. Fault decision is made by the probability of the trend of gradually accumulated errors applying Fuzzy logic, which are robust to instantaneous sensor signal noises. Reliability of fault diagnosis is verified under various fault simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1674-1680
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• 2009

This paper proposes an autonomous fault determination, fault zone isolation and fault restoration strategy based on the ethernet communication as a new attempt to solve the problem the of the existing central control method. In proposed method, The FRTU(Feeder Remote Terminal Unit)s on the feeder determines autonomously where the faulted zone is by exchanging the voltage and current information with neighbor FRTUs based on the network communication, and then separates the faulted zone in an nil-voltage status to make the protective device to reclose successively. In particular, the minimization of outage time and relational load balancing is archived by each interconnection switch which determines autonomously the load zone to be allocated among those zones after the sound outage zones was separated individually. Finally, to show effectiveness of the proposed fault restoration strategy, the several fault cases are simulated for the test distribution system, and the load balancing index of the proposed solution is compared with all of feasible solutions.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.4
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• pp.366-376
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• 2002

A sensor fault detection and isolation scheme(SFDIS) is adopted to improve the reliability of direct torque controlled induction motor drives and the experimental results are discussed. Major contributions include: experimental analysis of a few important sensor faults. design and implementation of the proposed SFDIS, and the fault tolerant control system(FTCS). Although the adopted SFDIS employs only one observer for residual generation, the system has the function of fault isolation that only multiple observer schemes can have. To verify the performance of the proposed scheme, the speed control system is designed for the 2.2kW direct torque controlled Induction motor. Hardware of the control system consists of a control board using TMS320OVC33 and a power stack using IPM. Experimental results for various type of sensor faults show the effectiveness of the SFDIS and the FTCS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.12
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• pp.1040-1047
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• 2012

This paper presents a fault diagnosis algorithm of control surfaces of small fixed-wing aircraft to reduce maintenance cost or to improve repair efficiency by estimation of fault occurrence or part replacement periods. The proposed fault diagnosis algorithm consists of ANPSD (Averaged Normalized Power Spectral Density), PCA (Principle Component Analysis), and GC (Geometric Classifier). ANPSD is used for frequency-domain vibration testing. PCA has advantage to extract compressed information from ANPSD. GC has good properties to minimize errors of the fault detection and isolation. The algorithm was verified by the accelerometer measurements of the scaled normal and faulty ailerons and the test results show that the algorithm is suitable for the detection and isolation of the control surface faults. This paper also proposes solutions for some kind of implementation problems.

• Earthquakes and Structures
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• v.22 no.1
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• pp.53-64
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• 2022

This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.