• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.765-771
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• 1998

An artificial neural network(NN) technique is developed for hardware redundant sensor validation. Since the measurement space is a continuous space with many operating regions, it is difficult to train a NN to correctly detect failure in an accurate measurement system. A conventional backpropagation NN is modified to include an additional preprocessing layer that extracts classification features from scalar measurements. This feature extraction means transform the measurement space to parity space. The NN is independent of the state variable being measured, the instrument range, and the signal tolerance. This NN resembles the parity space approach to signal validation, except that analytical parity equations are unneeded and the NN pattern recognition capability is utilized for decision making.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1002-1008
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• 2009

We consider a double faults detection and isolation problem using modified extended parity space approach for inertial measurement unit which use redundant inertial sensors. A redundant IMU which has a hardware redundant is composed of the cone shape because it is good for fault detection and isolation. We analyze the type of double faults and the reason why fault isolation performance is low. We propose modified extended parity space approach method using EPSA and the difference of sensor data.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.131-131
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• 2000

In this paper, a design method of a fault diagnosis filter for a system with multiplicative faults which cause to change its parameters is developed. Linear time-invariant systems are dealt with in discrete-time domain. The residual which is sensitive to a damage of control surface of an aircraft by parity space approach is defined. Next, the fault is isolated by a new decision logic. Control reconfiguration is achieved by the result of fault diagnosis. Finally, the feasibility of the method is illustrated with a simulation study of a fault diagnosis system for a damaged control surface of an aircraft.

• 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.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.398-404
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• 2012

A fault detection process is necessary for high integrity systems like satellites, missiles and aircrafts. Especially, the satellite has to be expected to detect faults autonomously because it cannot be fixed by an expert in the space. Faults can cause critical errors to the entire system and the satellite does not have sufficient computation power to operate a large scale fault management system. Thus, a fault detection method, which has less computational burden, is required. In this paper, we proposed a modified PCA (Principal Component Analysis) as a powerful fault detection method of redundant IMU (Inertial Measurement Unit). The proposed method combines PCA with the parity space approach and it is much more efficient than the others. The proposed fault detection algorithm, modified PCA, is shown to outperform fault detection through a simulation example.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.589-598
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• 2018

To maintain safety and reliability of reactors, redundant sensors are usually used to measure critical variables and estimate their averaged time-dependency. Nonhealthy sensors can badly influence the estimation result of the process variable. Since online condition monitoring was introduced, the online cross-calibration method has been widely used to detect any anomaly of sensor readings among the redundant group. The cross-calibration method has four main averaging techniques: simple averaging, band averaging, weighted averaging, and parity space averaging (PSA). PSA is used to weigh redundant signals based on their error bounds and their band consistency. Using the consistency weighting factor (C), PSA assigns more weight to consistent signals that have shared bands, based on how many bands they share, and gives inconsistent signals of very low weight. In this article, three approaches are introduced for improving the PSA technique: the first is to add another consistency factor, so called trend consistency (TC), to include a consideration of the preserving of any characteristic edge that reflects the behavior of equipment/component measured by the process parameter; the second approach proposes replacing the error bound/accuracy based weighting factor ($W^a$) with a weighting factor based on the Euclidean distance ($W^d$), and the third approach proposes applying $W^d$, TC, and C, all together. Cold neutron source data sets of four redundant hydrogen pressure transmitters from a research reactor were used to perform the validation and verification. Results showed that the second and third modified approaches lead to reasonable improvement of the PSA technique. All approaches implemented in this study were similar in that they have the capability to (1) identify and isolate a drifted sensor that should undergo calibration, (2) identify a faulty sensor/s due to long and continuous missing data range, and (3) identify a healthy sensor.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1440-1443
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• 1997

The optimal residual generator based on parity relation approach for the fault detection and isolation of a arge diesel engine actuator position servo system is presented. The closed-loop residual generator is designed to have robustness against modeling errors and noise. Main purpose of the fault detection and isolation system in the process is to detect and isolate two important faults, i.e., actuatro fault and fault of speed sensor, that, if not detected and compensated, degrade the overall control system performance. Simulation results are give to show the practical applicability of the fault detecrtion and isloation scherme.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.746-748
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• 1997

The parity relation approach for the fault detection and isolation (FDI) of a large diesel engine actuator position servo system is presented. Main purpose of the FDI system is to detect and isolate two important faults, actuator fault and sensor fault, that, if not detected and compensated, degrade the overall system performance. Simulation results are given to show the practical applicability of the FDI scheme.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.411-419
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• 2012

This paper proposes a new FDI(Fault Detection and Isolation) method, which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with one faulty sensor or two faulty sensors. In the system with two faulty sensors, the fault detection and isolation probability may be decreased when two faults are occurred between the sensors related to the large fault direction angle. Nonetheless, the previously suggested FDI methods to treat the two-faults problem do not consider the effect of the large fault direction angle. In order to solve this problem, this paper analyzes the effect of the large fault direction angle and proposes how to increase the fault detection and isolation probability. For the increase the detection probability, this paper additionally considers the fault type that is not detected because of the cancellation of the fault biases by the large fault direction angle. Also for the increase the isolation probability, this paper suggests the additional isolation procedure in case of two-faults. EPSA helps that the user can know the exact fault situation. The proposed FDI method is verified through Monte Carlo simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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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.