• Smart Structures and Systems
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• 제6권9호
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• pp.1007-1023
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• 2010

This paper describes the development and evaluation of an innovative TDR distributed moisture sensor. This sensor features advantages of being responsive to the spatial variations of the soil moisture content. The geometry design of the sensor makes it rugged for field installation. Good linear calibration is obtained between the sensor measured dielectric constant and soil physical properties. Simulations by the finite element method (FEM) are conducted to assist the design of this sensor and to determine the effective sampling range. Compared with conventional types of moisture sensor, which only makes point measurement, this sensor possesses distributed moisture sensing capability. This new sensor is not only easy to install, but also measures moisture distribution with much lower cost. This new sensor holds promise to significantly improve the current field instruments. It will be a useful tool to help study the influence of a variety of moisture-related phenomena on infrastructure performance.

• 센서학회지
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• 제28권5호
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• pp.277-283
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• 2019

In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.

• Structural Monitoring and Maintenance
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• 제7권1호
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• pp.1-12
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• 2020

Railway tracks are the direct supporting structures of the trains, which are vulnerable to produce large deformation under the temperature stress or subgrade settlement. The health status of track is critical, and the track should be routinely monitored to improve safety, lower the risk of excess deformation and provide reliable maintenance strategy. In this paper, the distributed optical fiber sensor was proposed to monitor the continuous deformation of the track. In order to validate the feasibility of the monitoring method, two deformation monitoring tests on one steel rail model in laboratory and on one real railway tack in outdoor were conducted respectively. In the model test, the working conditions of simply supported beam and continuous beam in the rail model under several concentrated loads were set to simulate different stress conditions of the real rail, respectively. In order to evaluate the monitoring accuracy, one distributed optical fiber sensor and one fiber Bragg grating (FBG) sensor were installed on the lower surface of the rail model, the strain measured by FBG sensor and the strain calculated from FEA were taken as measurement references. The model test results show that the strain measured by distributed optical fiber sensor has a good agreement with those measured by FBG sensor and FEA. In the outdoor test, the real track suffered from displacement and temperature loads. The distributed optical fiber sensor installed on the rail can monitor the corresponding strain and temperature with a good accuracy.

• 센서학회지
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• 제28권2호
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• pp.88-93
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• 2019

This paper is concerned with distributed fusion moving average prediction for continuous-time linear stochastic systems with multiple sensors. A distributed fusion with the weighted sum structure is applied to the optimal local moving average predictors. The distributed fusion prediction algorithm represents the optimal linear fusion by weighting matrices under the minimum mean square criterion. The derivation of equations for error cross-covariances between the local predictors is the key of this paper. Example demonstrates effectiveness of the distributed fusion moving average predictor.

• 센서학회지
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• 제28권3호
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• pp.146-151
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• 2019

This paper reports a sliding window filtering approach for ground moving targets with cross-correlated sensor noise and uncertainty. In addition, the effect of uncertain parameters during a tracking error on the model performance is considered. A distributed fusion sliding window filter is also proposed. The distributed fusion filtering algorithm represents the optimal linear combination of local filters under the minimum mean-square error criterion. The derivation of the error cross-covariances between the local sliding window filters is the key to the proposed method. Simulation results of the motion of the ground moving target a demonstrate high accuracy and computational efficiency of the distributed fusion sliding window filter.

• 제어로봇시스템학회논문지
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• 제18권8호
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• 한국군사과학기술학회지
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• 제14권1호
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• pp.123-131
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• 2011

In this paper, modeling and design of a distributed detection system are considered for an active sonar sensor network. The sensor network has a parallel configuration and it consists of a fusion center and a set of receiver nodes. A system with two receiver nodes is considered to investigate a theoretical aspect of design. To be specific, AND rule and OR rule are considered as the fusion rules of the sensor network. For the fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is obtained that maximizes the probability of detection given probability of false alarm. Numerical experiments were also performed to investigate the detection characteristics of a distributed detection system with multiple sensor nodes. The experimental results show how signal strength, false alarm probability, and the distance between nodes in a sensor field affect the system detection performances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3480-3500
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• 2017

Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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• pp.505-510
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• 2002

We have focused on the development of a fiber optic BOTDA (Brillouin Optical Time Domain Analysis) sensor system in order to measure temperature distributed on large structures. Also, we present a feasibility study of the fiber optic sensor to monitor the distributed temperature on a building construction. A fiber optic BOTDA sensor system, which has a capability of measuring the temperature distribution, attempted over several kilometers of long fiber paths. This simple fiber optic sensor system employs a laser diode and two electro-optic modulators. The optical fiber of the length of 1400 m was installed on the surfaces of the building. The change of the distributed temperature on the building construction was well measured by this fiber optic sensor. The temperature changed normally up to 4℃ through one day.

• 한국산학기술학회논문지
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• 제16권5호
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• pp.3421-3425
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• 2015

센서 네트워크에서 센서 노드의 구성은 연속적인 단일한 지역에 분포하기도 하지만 네트워크의 특성에 따라 여러 분리된 지역에 노드들이 분포하여 네트워크를 운영할 수 있다. 여러 지역에 분포된 센서 노드에 대한 자료 수집은 기존의 연속적인 지역의 자료 수집과는 특성이 달라질 수 있다. 따라서 분산된 지역에 의한 센서 네트워크의 운영은 기존의 연속적인 네트워크와는 다르게 운영될 수 있다. 본 논문에서는 분산된 지역에서 분포된 센서 노드에 대한 데이터 수집 방안에 대해 기술한다. 분산된 지역의 노드들은 이동 싱크와의 즉각적인 연결이 불가능할 수 있으므로 노드의 운영방안에 대해 고려하여야 한다. 이동 싱크와의 즉각적인 연결 방안에서는 실시간 데이터 전송이 가능하겠지만 분산 지역에서의 싱크 연결은 이동 싱크의 이동 특성을 고려하여야 한다. 본 논문에서는 시뮬레이션 결과를 통하여 제안 방안을 분석하고자 한다. 시뮬레이션 결과에서 분산 센서 네트워크에서 주기적 데이터 수집 방안이 임계치 방안에 의한 데이터 수집보다 전체 운영시간이 더 길게 나타냄을 보이고 있다.