• Journal of the Korean Geotechnical Society
• /
• v.34 no.9
• /
• pp.19-32
• /
• 2018

In this study, the applicability and practicality of landslides monitoring by using wireless sensor network (WSN) was analysed. WSN system consists of a sensor node for collecting and transmitting data using IEEE 802.14e standard, a gateway for collecting data and transmitting the data to the monitoring server. In the topology of the sensor network, a highly flexible and reliable mesh type was adopted, and three testbeds were chosen in each location of Seoul metropolitan area. Soil moisture sensors, tensiometers, inclinometers, and a rain gauge were installed at each testbed and sensor node to monitor the landslide. For the estimation of the optimal network topology between sensor nodes, the susceptibility assessment of landslides, forest density and viewshed analysis of terrain were conducted. As a result, the network connection works quite well and measured value of the volumetric water content and matric suction simulates well the general trend of the soil water characteristic curve by the laboratory test. As such, it is noted that WSN system, which is the reliable technique, can be applied to the landslide monitoring.

• Transactions of the Korean hydrogen and new energy society
• /
• v.20 no.1
• /
• pp.38-44
• /
• 2009

Recently, the research focused on fuel cell hybrid vehicles (FCHVs) is becoming an attractive solution due to environmental pollution generated by fossil fuel vehicles. The proper energy control strategy will result in extending the fuel cell lifetime, increasing of energy efficiency and an improvement of vehicle performance. Battery state of charge (SoC) is an important quantity and the estimation of the SoC is also the basis of the energy control strategy for hybrid electric vehicles. Estimating the battery's SoC is complicated by the fact that the SoC depends on many factors such as temperature, battery capacitance and internal resistance. In this paper, battery charging time estimated by SoC is studied by using the speed response and current response. Hybrid system is consist of a fuel cell unit and a battery in series connection. For experiment, speed response of vehicle and current response of battery were determined under different state of charge. As the results, the optimal battery charging time can be estimated. Current response time was faster than RPM response time at low speed and vice versa at high speed.

• Journal of the Korean Institute of Gas
• /
• v.16 no.1
• /
• pp.26-32
• /
• 2012

The autoignition temperature is one of the most important physical properties used to determine the flammability characteristics of chemical substances. Despite the needs of the experimental autoignition temperature data for the design of chemical plants, it is not easy to get the data. This study have built and compared partial least squares (PLS) and support vector machine (SVM) models to predict the autoignition temperatures of 503 organic compounds out of DIPPR 801. As the independent variables of the models, 59 functional groups were chosen based on the group contribution method. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, particle swarm optimization was used to get three parameters of SVM model. The PLS and SVM results of the average absolute errors for the whole data range from 58.59K and 29.11K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• Industrial Engineering and Management Systems
• /
• v.12 no.3
• /
• pp.244-253
• /
• 2013

In industries, shipping is an important issue in improving the forecasting accuracy of sales. This paper introduces a hybrid method and plural methods are compared. Focusing the equation of exponential smoothing method (ESM) that is equivalent to (1, 1) order autoregressive-moving-average (ARMA) model equation, a new method of estimating the smoothing constant in ESM had been proposed previously by us which satisfies minimum variance of forecasting error. Generally, the smoothing constant is selected arbitrarily. However, this paper utilizes the above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate the smoothing constant. Thus, theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This method is executed in the following method. Trend removing by the combination of linear and 2nd order nonlinear function and 3rd order nonlinear function is executed to the original production data of two kinds of bread. Genetic algorithm is utilized to search the optimal weight for the weighting parameters of linear and nonlinear function. For comparison, the monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.

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

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.9 s.240
• /
• pp.1235-1242
• /
• 2005

A district heating(DH) system supplies environmentally-friend heat and is appropriate for reduction of energy consumption and/or air pollutions. The DH transmission pipe, composed of supply and return pipes, has been used to transmit the heat and prevent heat loss during transportation. The two types of pipes are operated at a temperature of $75\~115^{\circ}C\;and\;40\~65^{\circ}C$, respectively, with an operating pressure of less than 1.568MPa. The objectives of this paper are to systematize data processing of transition temperature and investigate its effects on fatigue life of DH pipes. For the sake of this, about 5 millions temperature data were measured during one year at ten locations, and then available fatigue lift estimation schemes were examined and applied to quantify the specific thermal fatigue life of each pipe. As a result, a relational database management system as well as reliable fatigue lift evaluation procedures is established for Korean DH pipes. Also, since the prototypal evaluation results satisfied both cycle-based and stress-based fatigue criteria, those can be used as useful information in the future fer optimal design, operation and energy saving via setting of efficient condition and stabilization of water temperature.

• Smart Structures and Systems
• /
• v.21 no.5
• /
• pp.591-600
• /
• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.5
• /
• pp.427-436
• /
• 2002

This paper presents an implementation of high-dynamic performance of position sensorless motion control system of Reluctance Synchronous Motor(RSM) drives for an industrial servo system with direct torque control(DTC). The problems of high-dynamic performance and maximum efficiency RSM drives controlled by DTC are saturation of stator linkage flux and nonlinear inductance characteristics with various load currents. The accurate estimation of the stator flux and torque are obtained using stator flux observer of which a saturated inductance $L_d$ and $L_q$ can be compensated by adapting from measurable the modulus of the stator current and rotor position. To obtain fast torque response and maximum torque/current with varying load current, the reference command flux is ensured by imposing $I_{ds} = I_{qs}$. This control strategy is proposed to achieve fast response and optimal efficiency for RSM drive. In order to prove rightness of the suggested control algorithm, the actual experiment carried out at $\pm$20 and $\pm$1500 rpm. The developed digitally high-performance motion control system shown good response characteristic of control results and high performance features using 1.0kW RSM which has 2.57 Ld/Lq salient ratio.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.5
• /
• pp.434-444
• /
• 1991

An improved 2-D quadrature polar separable (QPS) filter and its applications to texture processing are discussed in thie paper. The frequency response of the filter consists of two independent parts. The first is a radial weighting function based on the prolate spheridal sequence(PSS). The second is the same orientational function of the angle as in the Knutsson filter. The new filter is suboptimal in the energy loss because we let the polar angle function approximate the radial weighting function as in the 2-D Cartesian filter composed of two PSS's. It is easy to control as it depends only upon the design specification of the bandwidth, the drectional agnle, and the central freqneucy. Also the filter is circularly more symmetric in the frequency domain than the Knutsson filter. In order to estimate the orientation and the frequency component of loca textures in the frequency domain, some applications of the new filter, such as the generation of synthetic textures, the estimation of texture orientations, and texture segementations, are discussed.

• The KIPS Transactions:PartD
• /
• v.10D no.7
• /
• pp.1127-1136
• /
• 2003

Estimation of software project cost, effort and duration in the early stage of software development cycle is a difficult and key problem in software engineering. Most of models estimate the development effort using the function point that is measured from the requirement specification. This paper presents optimal team size and duration prediction based on function point in order to provide information that can be used as a guide in selecting the most Practical and productive team size for a software development project. We introduce to productive metrics and cost for decision criteria of ideal team size and duration. The experimental is based on the analysis of 300 development and enhancement software project data. These data sets are divide in two subgroups. One is a development project; the other is a maintenance project. As a result of evaluation by productivity and cost measured criteria in two subgroups, we come to the conclusion that the most successful projects has small teams and minimum duration. Also, I proposed that predictive model for team sire and duration according to function point size based on experimental results. The presented models gives a criteria for necessary team site and duration according to the software size.