• Journal of the Korean Society for Precision Engineering
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• v.27 no.11
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• pp.30-36
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• 2010

Previous researches show that linearly integrated Hall sensor arrays (LIHaS) can detect cracks in the steel structure fast and effectively This paper proposes an algorithm that estimates the size and shape of cracks for the developed LIHaS. In most nondestructive testing (NDT), just crack existence and location are obtained by processing 1-dimensional data from the sensor that scans the object with relative speed in single direction. The proposed method is composed with two steps. The first step is constructing 2-dimensionally mapped data space by combining the converted position data from the time-based scan data with the position information of sensor arrays those are placed in the vertical direction to the scan direction. The second step is applying designed Laplacian filter and smoothing filter to estimate the size and shape of cracks. The experimental results of express train wheels show that the proposed algorithm is not only more reliable and accurate to detecting cracks but also effective to estimate the size and shape of cracks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2299-2318
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• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.363-370
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• 2020

This paper reports the results of an experimental study using the BOTDR sensor to detect the unbonded location of attached CFRP sheet for structural rehabilitation. A specimens with the unattached CFRP sheet were fabricated for this study, on which BOTDR sensor was attached with a nylon net. During the flexural test of the specimens, the strain of the CFRP sheet was measured using the BOTDR sensor and electric resistance gauges. From the results, it was confirmed that the strain distribution obtained through the BOTDR sensor can be effectively used to visualize and detect the unbonded position of the CFRP sheet. In addition, In addition, the strain measured by the BOTDR sensor was found to be more effective in analyzing the overall structure behavior than the electric resistance strain gauge. The development of a BOTDR sensor with a measuring longth of less than 100 mm will enable accurate detection of the local unbonded position of the CFRP sheet.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.424-427
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• 2009

This paper reposes a novel tracking algerian for efficiency improvement of photovoltaic(PV) system using sensor method PV system of sensor method is exactly impossible to track a sun position when insolation is low or rapidly changed by the clouds and fogs. Also, in this case, tracking device is occurred energy consumption by unnecessary operating. This statement of reason, real power of PV system is not increased than fixed PV system in specified location. Therefore, this paper proposes a novel ticking algorithm considered insolation for efficiency improvement of PV system using sensor method And this paper analyzes the generation volume and proves the validity of proposed algorithm as compared with the conventional PV tracking system using sensor method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2192-2199
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• 2009

This paper proposes a novel tracking algorithm for efficiency improvement of photovoltaic(PV) system using sensor method. PV system of sensor method is exactly impossible to track a sun position when insolation is low or rapidly changed by the clouds and fogs. Also, in this case, tracking device is occurred energy consumption by unnecessary operating. This statement of reason, real power of PV system is not increased than fixed PV system in specified location. Therefore, this paper proposes a novel tracking algorithm considered insolation for efficiency improvement of PV system using sensor method. And this paper analyzes the generation volume and proves the validity of proposed algorithm as compared with the conventional PV tracking system using sensor method.

• Ocean Systems Engineering
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• v.9 no.4
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• pp.391-407
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• 2019

Tracking the location (position) of a surface or underwater marine vehicle is important as part of guidance and navigation. While the Global Positioning System (GPS) works well in an open sea environment but its use is limited whenever testing scaled-down models of such vehicles in the laboratory environment. This paper presents the design, development and implementation of a low energy ultrasonic augmented single beacon-based localization technique suitable for such requirements. The strategy consists of applying Extended Kalman Filter (EKF) to achieve location tracking from basic dynamic distance measurements of the moving model from a fixed beacon, while on-board motion sensor measures heading angle and velocity. Iterative application of the Extended Kalman Filter yields x and y co-ordinate positions of the moving model. Tests performed on a free-running ship model in a wave basin facility of dimension 30 m by 30 m by 3 m water depth validate the proposed model. The test results show quick convergence with an error of few centimeters in the estimated position of the ship model. The proposed technique has application in the real field scenario by replacing the ultrasonic sensor with industrial grade long range acoustic modem. As compared with the existing systems such as LBL, SBL, USBL and others localization techniques, the proposed technique can save deployment cost and also cut the cost on number of acoustic modems involved.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.155-162
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• 2007

For providing smart home service, middleware technologies for electronic appliance control by network and user location information for location based service are important. Recently research using ultrasonic and radio signal are affected by the obstacle. In this paper, we suggest inertial sensor that is not affected by the obstacle. Also, we use RFID for initializing position. It solve error accumulation and position initialize problem. In this paper, we suggest following system for smarthome service and localization. This system are composed smarthome middleware, user localization system on middleware, inertial sensor and RFID Reader. This system shows operation without affect of obstacle in smarthome environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.57-63
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• 2008

Recently, OGC(Open Geospatial Consortium) take the lead in SWE(Sensor Web Enablement) research that collection various context information from sensor networks and show it on map by web. OGC SWE WG(Working Group) defines a standard encoding about realtime spatiotemporal appear geographical feature, sensing data and support web services. This paper proposes a visualization scheme of sensing data based location on 2D maps. We show realtime sensing data on moving node that mapping GPS data on map. First, we present an algorithm and procedure that location information change to position of maps for visualization sensing data based on 2D maps. For verifying that algorithm and scheme, we design and implement a program that collecting GPS data and sensing data, and displaying application on 2D maps. Therefore we confirm effective visualization on maps based on web which realtime image and sensing data collected from sensor network.