• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1814-1820
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• 2018

State estimation of power systems has become vital in recent days of power operation and control. SCADA and EMS are intended for the state estimation and to communicate and monitor the systems which are operated at specified time. Although various methods are used we can achieve the better results by using PMU technique. On placing the PMU, operating time is reduced and making the performance reliable. In this paper, PMU placement is done in two ways. Those are 'optimal technique with pruning operation' and 'depth of unobservability' considering incomplete and complete observability of a network. By Depth of Unobservability Number of PMUs are reduced to attain Observability of the network. Proposed methods are tested on IEEE 14, 30, 57, SR-system and Sub systems (1, 2) with bus size of 270 and 444 buses. Along with achieving complete observability analysis, single PMU loss condition is also achieved.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.5
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• pp.400-408
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• 2023

The tracking accuracy of buoy-based LBL(Long Base Line) systems can be significantly influenced by sea environmental conditions. Particularly, the position of buoys that may have drifted due to sea currents. Therefore it is necessary to predict and optimize the drifted-buoy positions in the deploying step. This research introduces a free-drift simulation model using ocean data from the European CMEMS. The simulation model's predictions are validated by comparing them to actual sea buoy drift tracks, showing a substantial match in averaged drift speed and direction. Using this drift model, we optimize the initial buoy layout and compare the tracking performance between the center hexagonal layout and close track layout. Our results verify that the optimized layout achieves lower tracking errors compared to the other two layout.

• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.35-40
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• 2013

In the eLoran navigation system, the dominant deterioration factors of navigation accuracy are the TOA measurement errors on user receiver and the GDOP between the receiver and the transmitters. But if the ASF data measured at dLoran reference station are provided for users through the Loran data channel, it will be possible to correct the TOA measurement errors. The position accuracy can be determined by the DOP depending on the geometry of receiver-transmitters, and their optimal placement improves the navigation accuracy. In this study we determined the geometric placement in case of up to six stations, and evaluated the performance of position accuracy for the receiver-transmitter geometry set of eLoran stations. The proposed geometry of eLoran stations can be referred for the construction of eLoran infrastructure meeting the capability of HEA for maritime, and time/frequency users in Korea.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.399-402
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• 2002

In this study, we constructed a four-channel impedance measurement system including a two-channel goniometer to analyze human arm movement. Impedances and joint angles were simultaneously measured for wrist and elbow movements. As the impedance changes resulting from wrist and elbow movements depended heavily on electrode placement, we determined the optimal electrode configurations for those movements by searching for high correlation coefficients, large impedance changes, and minimum interferences in ten subjects (age: 29+6). Our optimal electrode configurations showed very strong relationships between the wrist joint angle and forearm impedance (correlation coefficient = 0.95+0.04), and between the elbow joint angle and upper arm impedance (correlation coefficient = -0.98+0.02). Although the measured impedances changes of the wrist (1.1+1.5 ohm) and elbow (-5.0+2.9 ohm) varied among individuals, the reproducibilities of wrist and elbow impedance changes of five subjects were 5.8+1.8 % and 4.6+1.4 % for the optimal electrode pairs, respectively. We propose that this optimal electrode configuration would be useful for future studies involving the measurement of accurate arm movements by impedance method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.2
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• pp.145-155
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• 2002

It is essential for health monitoring of a cable-stayed bridge to provide more accurate and enough information from the sensors. In experimental modal testing, the chosen measurement locations and the number of measurements have a major influence on the quality of the results. The choice is often difficult for complex structures like a cable-stayed bridge. It is extremely important a cable-stayed bridge to minimize the number of sensing operations required to monitor the structural system. In order to obtain the desired accuracy for the structural test, several issues must take into consideration. Two important issues are the number and location of response sensors. There are usually several alternative locations where different sensors can be located. On the other hand, the number of sensors might be limited due to economic constraints. Therefore, techniques such as methodologies, algorithms etc., which address the issue of limited instrumentation and its effects on resolution and accuracy in health monitoring systems are paramount to a damage diagnosis approach. This paper discusses an optimum sensor placement criterion suitable to the identification of structural damage for continuous health monitoring. A Kinetic Energy optimization technique and an Effective Independence Method are analyzed and numerical and theoretical issues are addressed for a cable-stayed bridge. Its application to a cable-stayed bridge is discussed to optimize the sensor placement for identification and control purposes.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.3-12
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• 2010

In previous studies, the digital measurement systems and analysis algorithms were developed by using the related techniques, such as the aerial photograph detection and high resolution satellite image process. However, these studies were limited in 2-dimensional geo-processing. Therefore, it is necessary to apply the 3-dimensional spatial information and coordinate system for higher accuracy in recognizing and locating of geo-features. The objective of this study was to develop a stochastic algorithm for the optimal sensor placement using the 3-dimensional spatial analysis method. The 3-dimensional information of the LiDAR was applied in the sensor field algorithm based on 2- and/or 3-dimensional gridded points. This study was conducted with three case studies using the optimal sensor placement algorithms; the first case was based on 2-dimensional space without obstacles(2D-non obstacles), the second case was based on 2-dimensional space with obstacles(2D-obstacles), and lastly, the third case was based on 3-dimensional space with obstacles(3D-obstacles). Finally, this study suggested the methodology for the optimal sensor placement - especially, for ground-settled sensors - using the LiDAR data, and it showed the possibility of algorithm application in the information collection using sensors.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.287-297
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• 2019

Monitoring for the physiological state of a solider is essential to the realization of individual combat system. Despite all efforts over the last decades, there is no report to point out the optimal location of the wearable biosensors considering both monitoring accuracy and operational robustness. In response, we quantitatively measure body temperature and heartrate from 34 body parts using 2 kinds of biosensor arrays, each of which consists of a thermocouple(TC) sensor and either a photoplethysmography(PPG) sensor or an electrocardiography(ECG) sensor. The optimal location is determined by scoring each body part in terms of signal intensity, convenience in use, placement durability, and activity impedance. The measurement leads to finding the optimal location of wearable biosensor arrays. Thumb and chest are identified as best body parts for TC/PPG sensors and TC/ECG sensors, respectively. The findings will contribute to the successful development of individual combat system.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Smart Structures and Systems
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• v.30 no.4
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• pp.339-351
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• 2022

Evaluating the current condition of existing structures is of primary importance for economic and safety reasons. This can be addressed by Structural System Identification (SSI). A reliable static SSI depends on well-designed sensor configuration and loading cases, as well as efficient parameter estimation algorithms. Static SSI by the Measurement Error-Minimizing Observability Method (MEMOM) is a model-based deterministic static SSI method that could estimate structural parameters from static responses. In the current state of the art, this method is only applicable when structures are subjected to one loading case. This might lead to lack of information in some local regions of the structure (such as the null curvatures zones). To address this issue, the SSI by MEMOM using multiple loading cases is proposed in this work. Observability equations obtained from different loading cases are concatenated simultaneously and an optimization procedure is introduced to obtain the estimations by minimizing the discrepancy between the predicted response and the measured one. In addition, a Genetic-Algorithm (GA)-based Optimal Sensor Placement (OSP) method is proposed to tackle the OSP problem under multiple static loading cases for the very first time. In this approach, the Fisher Information Matrix (FIM)'s determinant is used as the metric of the goodness of sensor configurations. The numerical examples of a 3-span continuous bridge and a 13-story frame, are analyzed to validate the applicability of the extended SSI by MEMOM and the GA-based OSP method.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.