• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1167-1169
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• 2009

Multipath routing in wireless sensor networks has been proven to provide with increased data delivery ratio, security, robustness to node and link failures, network throughput, etc. However, the energy cost for multiple routes construction and their maintenance is very high. This paper proposes a sink-initiated, node-disjoint multipath routing protocol for static wireless sensor networks that significantly minimizes the route construction messages and thereby saves the critical batter energy of sensor nodes. It also distributes the traffic load spatially over many nodes in the forwarding paths, which ensures balanced energy consumption in the network and thereby increases the network lifetime. The simulation results show that it decreases the routing overhead as well as the standard deviation of nodes' residual energies.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2331-2334
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• 2003

The basic difference between the EKF(Extended Kalman Filter) and UKF(Unscented Kalman Filter) stems from the manner in which Gaussian random variables(GRV) are represented for propagating through system dynamics. In the EKF, the state distribution is approximated by a GRV, which is then propagated analytically through the first-order linearization of the nonlinear system. This can possibly introduce large errors in the true posterior mean and covariance of the transformed GRV, which may lead to sub-optimal performance and sometimes divergence of the filter. However, the UKF addresses this problem by using a deterministic sampling approach. The state distribution is also approximated by a GRV, but is now represented using a minimal set of carefully chosen sample points. These sample points completely capture the true mean and covariance of the GRV, and UKF captures the posterior mean and covariance accurately up to the 2nd order(Taylor series expansion) for any nonlinearity. This paper utilizes the UKF to determine spacecraft orbit when only magnetometer is available. Several catastrophic failures of spacecraft in orbit have been attributed to failures of the spacecraft mission. Recently studies on contingency-major sensor failure cases- have been performed. For mission success, contingency design or plan should be implemented in case of a major sensor failure. Therefore the algorithm presented in this paper can be used for a spacecraft without GPS or contingency design in case of GPS failure.

• Advances in aircraft and spacecraft science
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• v.4 no.1
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• pp.53-64
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• 2017

Aerospace Launch Vehicles (ALV) are generally designed with high reliability to operate in complete security through fault avoidance practices. However, in spite of such precaution, fault occurring is inevitable. Hence, there is a requirement for on-board fault recovery without significant degradation in the ALV performance. The present study develops an advanced fault recovery strategy to improve the reliability of an Aerospace Launch Vehicle (ALV) navigation system. The proposed strategy contains fault detection features and can reconfigure the system against common faults in the ALV navigation system. For this purpose, fault recovery system is constructed to detect and reconfigure normal navigation faults based on the sliding mode observer (SMO) theory. In the face of pitch channel sensor failure, the original gyro faults are reconstructed using SMO theory and by correcting the faulty measurement, the pitch-rate gyroscope output is constructed to provide fault tolerant navigation solution. The novel aspect of the paper is employing SMO as an online tuning of analytical fault recovery solution against unforeseen variations due to its hardware/software property. In this regard, a nonlinear model of the ALV is simulated using specific navigation failures and the results verified the feasibility of the proposed system. Simulation results and sensitivity analysis show that the proposed techniques can produce more effective estimation results than those of the previous techniques, against sensor failures.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.814-826
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• 2023

Sensor faults in nuclear power plant instrumentation have the potential to spread negative effects from wrong signals that can cause an accident misdiagnosis by plant operators. To detect sensor faults and make accurate accident diagnoses, prior studies have developed a supervised learning-based sensor fault detection model and an accident diagnosis model with faulty sensor isolation. Even though the developed neural network models demonstrated satisfactory performance, their diagnosis performance should be reevaluated considering real-time connection. When operating in real-time, the diagnosis model is expected to indiscriminately accept fault data before receiving delayed fault information transferred from the previous fault detection model. The uncertainty of neural networks can also have a significant impact following the sensor fault features. In the present work, a pilot study was conducted to connect two models and observe actual outcomes from a real-time application with an integrated system. While the initial results showed an overall successful diagnosis, some issues were observed. To recover the diagnosis performance degradations, additive logics were applied to minimize the diagnosis failures that were not observed in the previous validations of the separate models. The results of a case study were then analyzed in terms of the real-time diagnosis outputs that plant operators would actually face in an emergency situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.11
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• pp.911-923
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• 2013

Multipath routing is one of challenging issues for improving the reliability of end-to-end data delivery in wireless sensor networks. Recently, a disjointedness and management of path have been studying to enhance the robustness and efficiency of the multipath routing. However, previous multipath routing protocols exploit the disjointed multipath construction method that is not to consider the wireless communication environment. In addition, if a path failures is occurred due to the node or link failures in the irregular network environment, they maintain the multipath through the simple method that to construct a new extra path. Even some of them have no a method. In order to cope with the insufficiency of path management, a hole detouring scheme, to bypass the failures area and construct the new paths, was proposed. However, it also has the problem that requires a heavy cost and a delivery suspension to the some or all paths in the hole detouring process due to the centralized and inflexible path management. Due to these limitations and problems, the previous protocols may lead to the degradation of data delivery reliability and the long delay of emergency data delivery. Thus, we propose a flexible disjoint multipath routing protocol which constructs the radio disjoint multipath by considering irregular and constrained wireless sensor networks. It also exploits a localized management based on the path priority in order to efficiently maintain the flexible disjoint multipath. We perform the simulation to evaluate the performance of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.288-294
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• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.122-130
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• 2010

Seventy percent of Korea's national territory is covered with mountains, and the land is frequently exposed to typhoons and localized torrential downpours, particularly in July through September. For this reason, slope failure is one of the most frequent types of natural disasters in Korea. To prevent the damage caused by slope failure, the Korean government, academia and industry have strived together to develop and install a wired system for monitoring slope failures. However, conventional wired monitoring systems have been reported to have limitations, such as possible system errors caused by lightning, and the difficulties of restoration and management of the systems. To solve these problems, this research suggests a USN-based monitoring system for slope failures. First, the trend of slope measurement and USN technology was analyzed, and then the current status of damage caused by slope failures in Korea was reviewed. Next, a USN-based monitoring scenario for slope failures, incorporating both USN and slope monitoring technique, was developed. Finally, sensors were decided based on the developed scenario. It is expected that the results of this study will be utilized as fundamental data for the development of monitoring prototype systems for slope failures in the future. The development of the USN-based monitoring system for slope failures and its application in the field will also ultimately contribute to the prevention of slope failures and the minimization of related damage.

• Smart Structures and Systems
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• v.16 no.2
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• pp.329-345
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• 2015

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order $H_{\infty}$ FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

• Journal of IKEEE
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• v.20 no.4
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• pp.449-453
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• 2016

Failures would occur because of the hostile nature environment in Wireless Sensor Networks (WSNs) which is deployed randomly. Therefore, considering faults in WSNs is essential when we design WSN. This paper classified fault model in the sensor node. Especially, this paper proposed new error correcting code scheme and fault recovery algorithm in the CH(Cluster Head) node. For the range of the small size information (<16), the parity size of the proposed code scheme has the same parity length compared with the Hamming code, and it has a benefit to generate code word very simple way. This is very essential to maintain reliability in WSN with increase power efficiency.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.219-222
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• 2023

Partial discharges (PD) have long been recognized as a major contributing factor to catastrophic failures in high-power equipment. As the demand for high voltage direct current (HVDC) facilities continues to rise, the significance of on-line and real-time monitoring of PD becomes increasingly prominent. In this study, we have designed, fabricated, and characterized a highly sensitive and cost-effective PD sensor comprising a pair of copper electrodes with different arc lengths. The key advantage of our sensor is its non-invasive nature, as it can be installed at any location along the entire power cable without requiring structural modifications. In contrast, conventional PD sensors are typically limited to installation at cable terminals or insulation joint boxes, often necessitating invasive alterations. Our PD sensor demonstrates exceptional accuracy in estimating PD location, with a success rate exceeding 95% in the straight sections of the power cable and surpassing 89% in curved sections. These remarkable characteristics indicate its high potential for realtime and on-line detection of PD.