• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.4
• /
• pp.364-370
• /
• 2004

In this paper, we propose a FDI method, which comes from singular value decomposition of measurement matrix fur redundant sensors. We analyze the performance of the proposed FDI method by comparing with the GLT method in two ways such as FDI performance and GN＆C performance. Also, we propose a GN＆C performance index by combining FDI and GN＆C performance.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.7 no.3 s.18
• /
• pp.140-148
• /
• 2004

Fault detection and isolation(FDI) and reconfigurable flight control system provide better survivability even though actuator faults occur. In this study, a new fault detection and isolation algorithm is proposed using fuzzy logic. When the FDI system detects the actuator fault, the fuzzy logic investigates the state variables to find which actuator has fault. Proposed fuzzy detection algorithm detect not only a single fault but also multiple faults. After detecting the fault, the reconfigurable flight control system begins operating for compensating the effects of the fault. A numerical simulation using six degree-of-freedom nonlinear aircraft model is performed to verity the performance of the proposed fault detection and isolation scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2188-2191
• /
• 2005

We consider a fault detection and isolation problem for inertial navigation systems which use redundant inertial sensors. We propose a FDI method using average of multiple parity vectors which reduce false alarm and wrong isolation, and improve correct isolation. We suggest the number of redundant sensors required to isolate simultaneous faults. The performance of the proposed FDI algorithm is analyzed by Monte-Carlo simulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.3
• /
• pp.200-206
• /
• 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 Institute of Control, Robotics and Systems
• /
• v.17 no.10
• /
• pp.960-966
• /
• 2011

In this paper, an $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ fault detection and isolation (FDI) observer design problem is investigated for discrete-time delayed systems. To that end, a bank consisting of the sensor's number of observers is introduced. Each residual should be sensitive to a certain partial group of faults, but robust against the disturbance as far as possible. We formulate this multiobjective FDI problem as $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ observers design problem. Sufficient design condition is expressed as iterative linear matrix inequalities. The fault is then detected and isolated by evaluating the residuals through an FDI decision logic. A computer simulation is provided for verification of the proposed technique.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2227-2229
• /
• 2004

Fault Detection and Isolation(FDI) schemes using unknown input functional observers with very low order are presented. These schemes resolve the major practical difficulties with all FDI systems employing multiple observers for residual generation and can be implemented by the use of microprocessors that are normally used in commercial processes mainly due to the simplicity of the residual generation block. Various design objectives including detection, isolation, estimation and compensation of instrument fault/or process fault are achievable with these schemes. The proposed FDI scheme is applied to an inverted pendulum control system for instrument fault detection.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.5
• /
• pp.797-806
• /
• 2012

Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

• Journal of Power Electronics
• /
• v.14 no.5
• /
• pp.967-979
• /
• 2014

This paper focuses on speed and current sensor fault detection and isolation (FDI) for induction motor (IM) drives. A new, accurate and high-efficiency FDI approach is proposed so that a system can continue operating with good performance even in the presence of speed sensor faults, current sensor faults or both. The proposed three paralleled adaptive observers are capable of current sensor fault detection and localization. By using observers, the rotor flux and rotor speed can be estimated which allows the system to run under the speed sensorless vector control mode when a speed sensor fault occurs. In order to detect speed sensor faults, a threshold-based scheme is proposed. To verify the feasibility and effectiveness of the proposed FDI strategy, experiments are carried out under different conditions based on a dSPACE DS1104 induction motor drive platform.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.1
• /
• pp.68-79
• /
• 1998

In this paper, we propose a model-based FDI(fault detetion and isolation) algorithm to detect and isolate fault in a linear system. The proposed algorithm is gased on an HFC(hydrid fault classifier) which consists of an FCART2(fault classifier by ART2 neural network) and an FCFM(fault classifier by fault models) which operate in parallel to isolate faults. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation. When a change in the system occurs, the estimated parameters go through a transition zone in which errors between the system output and the stimated output and the estimated output cross a predetermined thrseshold, and in this zone the estimated parameters are tranferred to the FCART2 for fault isolation. On the other hand, once a fault in the system is detected, the FCFM statistically isolates the fault by using the error between ach fault model out put and the system output. From the computer simulation resutls, it is verified that the proposed model-based FDI algorithm can be performed successfully to detect and isolate faults in a position control system of a DC motor.

• Aerospace Engineering and Technology
• /
• v.6 no.2
• /
• pp.150-156
• /
• 2007

In this paper, we focus on the fault detection and isolation(FDI) method for inertial navigation system with three two-degree of freedom dynamically tuned gyros(DTG) on orthogonal sensor configuration. we propose the FDI method which can detect the fault of each DTGs rather than the fault of each sensing axis. The proposed FDI method is separated into two FDI modules according to the fault magnitude in order to improve the reliability of fault detection information. For large fault detection, only instantaneous DTG measurement is used to detect a fault DTG within a short time. For small fault detection, the integrated value of DTG measurements are used to detect a fault DTG. It takes a more time to detect a fault but it serves more reliable fault detection information. Using the proposed FDI method with consideration of DTG fault characteristic, we could find out a fault DTG successfully.