• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.155-160
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• 2007

A fault detection and isolation (FDI) problem is considered for inertial sensors, such as gyroscopes and accelerometers and a new FDI method for double faults is proposed using reduced-order parity vector. The reduced-order parity vector (RPV) algorithm enables us to isolate double faults with 7 sensors. Averaged parity vector is used to reduce false alarm and wrong isolation, and to improve correct isolation. The RPV algorithm is analyzed by Monte-Carlo simulation and the performance is given through fault detection probability, correct isolation probability, and wrong isolation probability.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1648-1656
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• 2018

The configuration of redundant inertial sensors are very important when considering navigation performance and fault detection and isolation (FDI) performance. By constructing a redundant sensor system using multiple inertial sensors, it is possible to improve the navigation performance and fault detection and isolation performance, which are highly related to the sensor configuration and allocation. In order to deploy multiple MEMS inertial measurement units effectively, a configuration and allocation methods considering navigation performance, fault detection and isolation performance, and lever arm effect in one plane are presented, and the performance is analyzed through simulation in this research. From the results, it is confirmed that the proposed configuration and allocation method can improve navigation, FDI, and lever arm effect rejection performances more effectively by more than 70%.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.4-116
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• 2001

We consider a robust configuration problem of inertial sensors for inertial navigation system(INS). Fault detection and isolation(FDI) is necessary to improve reliability of the system. For FDI, there used to be more than three mutually orthogonal sensors and thus we have to consider configuration methods of sensors. Various studies in this area have been done, but the former results did not consider effect of uncertainty(misalignment, scale factor error) to determine the configuration of the sensors. In this paper robust configuration of sensors is proposed through sensitivity analysis. Also total least square(TLS) method ...

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.104-109
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• 2007

This paper is about a redundancy management system design for the Smart UAV(unmanned aerial vehicle) which utilizes the tilt..rotor mechanism. In order to meet the safety requirement on the PLOC(probability of loss of control) of $1.7{\times}10^{-5}$ per flight hour for FCS (flight control system) failures, a digital FCS is mechanized with a dual redundant structure. A fault detection system which is composed of a CCM(cross channel monitor) and analytic redundancy using the Kalman filtering is designed, and its effectiveness is evaluated through experiments. A threshold level and persistence count for managing redundant sensors are designed based on the statistical analysis of the FCS sensors. To increase the survivability of the UAV after the loss of critical sensors in the SAS(stability augmentation system) and to provide reference information for a tie-breaking condition at which an ILM(in-line monitor) cannot distinguish the faulty channel between two operating ones, the Kalman filter approach is investigated.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.8-13
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• 2014

We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4804-4822
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• 2017

Coverage problem is a research hot spot in directional sensor networks (DSNs). However, the major problem affecting the performance of the current coverage-enhancing strategies is that they just optimize the coverage of networks, but ignore the maximum number of sleep sensors to save more energy. Aiming to find an approximate optimal method that can cover maximum area with minimum number of active sensors, in this paper, a new scheduling algorithm based on learning automata is proposed to enhance area coverage, and shut off redundant sensors as many as possible. To evaluate the performance of the proposed algorithm, several experiments are conducted. Simulation results indicate that the proposed algorithm have effective performance in terms of coverage enhancement and sleeping sensors compared to the existing algorithms.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.485-493
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• 2004

Open-loop position estimation methods are commonly used in mobile robot applications. Their strength lies in the speed and simplicity with which an estimated position is determined. However, these methods can lead to inaccurate or unreliable estimates. Two position estimation methods are developed in this paper, one using a single optical flow sensor and a second using two optical sensors. The first method can accurately estimate position under ideal conditions and also when wheel slip perpendicular to the axis of the wheel occurs. The second method can accurately estimate position even when wheel slip parallel to the axis of the wheel occurs. Location of the sensors is investigated in order to minimize errors caused by inaccurate sensor readings. Finally, a method is implemented and tested using a potential field based navigation scheme. Estimates of position were found to be as accurate as dead-reckoning in ideal conditions and much more accurate in cases where wheel slip occurs.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.7
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• pp.1169-1177
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• 1994

The function estimation characteristics of neural networks can be used sensor signal estimation of the nuclear power plants. In case of applying the neural network to the signal estimation of redundant sensors, it is an important problem that the redundant sensor signals used as the input signals of neural network should be validated. In this paper, we simplify the conventional parity space method in order to input the validated signal to the neural network and lso propose the sensor signal validation method, which estimates the reliable sensor output combining the neural network with the simplified parity space method. The acceptability of the proposed process variable estimation method is demonstrated by using the simulation data in safety injection accident of the nuclear power plant.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.47-53
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• 2011

When some sensors under Wireless Sensor Networks fail or become energy-exhausted, redundant mobile sensors might be moved to recover the sensing holes. Within rugged terrain where wheeled sensors are unsuitable, other type of mobile sensors, such as hopping sensors, are needed. In this paper, we address the problem of relocating hopping sensors to the detected sensing holes. Recent study for this work considered the relocation using the shortest path between clusters; however, the shortest path might be used repeatedly and create other sensing holes. In order to overcome the mentioned problem, we propose relocation schemes using the most disjointed paths or multi-paths. Simulation results show that the proposed schemes guarantee more balanced migration distributions of efficient sensors and higher movement success ratios of required sensors than those of the shortest path-based scheme.