• Smart Structures and Systems
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• v.12 no.3_4
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• pp.309-325
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• 2013

Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.

• Smart Structures and Systems
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• v.4 no.6
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• pp.779-794
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• 2008

Observer-based fault detection and isolation (FDI) filter design method is a model-based method. By carefully choosing the observer gain, the residual outputs can be projected onto different independent subspaces. Each subspace corresponds to the monitored structural element so that the projected residual will be nonzero when the associated structural element is damaged and zero when there is no damage. The key point of detection filter design is how to find an appropriate observer gain. This problem can be interpreted in a geometric framework and is found to be equivalent to the problem of finding a decentralized static output feedback gain. But, it is still a challenging task to find the decentralized controller by either analytical or numerical methods because its solution set is, generally, non-convex. In this paper, the concept of detection filter and iterative LMI technique for decentralized controller design are combined to develop an algorithm to compute the observer gain. It can be used to monitor structural element state: healthy or damaged. The simulation results show that the developed method can successfully identify structural damages.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.905-910
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• 2012

This paper reports an investigation of pulse width modulation (PWM) techniques for twophase brushless DC (BLDC) motors fed by a two-phase eight-switch inverter in a fan application. The three-phase BLDC motor is widely applied in industry; however, a lower-cost two-phase BLDC motor and drive circuit has been greatly in demand in recent years. In this paper, we introduce a mathematical model of the two-phase BLDC motor with sinusoidal back electromotive forces (EMFs) based on traditional three-phase BLDC motors. To simplify the drive algorithm and speed up its application, we analyze the principle of block commutation for a two-phase BLDC motor drive in the 180-electricaldegree conduction mode, and we further propose five PWM schemes to improve the commutation performance of the two-phase BLDC drive. The effectiveness of the proposed PWM methods is verified through experiments.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.312-320
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• 2003

Recently there is a growing interest in mobile cellular network providing multimedia service. However, the link bandwidth of mobile cellular network is not sufficient enough to provide satisfactory services to users. To overcome this problem, an adaptive framework has been proposed. In this study, we propose a new method of estimating DPR(Degradation Period Ratio) in an adaptive multimedia network where the bandwidth of ongoing call can be dynamically adjusted during its lifetime. DPR is a QoS(Quality of Service) parameter which represents the ratio of allocated bandwidth below a pre-defined target to the whole service time of a call. We improve estimation method of DPR using DTMC(Discrete Time Markov Chain) model by calculate mean degradation period, degradation probability more precisely than in existing studies. Under Threshold CAC(Call Admission Control) algorithm, we present analytically how to guarantee QoS to users and illustrate the method by numerical examples. The proposed method is expected to be used as one of CAC schemes in guaranteeing predefined QoS level of DPR.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.199-206
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• 2008

The introduction of competition in electricity markets emphasizes the importance of sufficient transmission capacities to guarantee effective power transactions. Therefore, for the economic and stable electric power system operation, transmission security constrains should be incorporated into the dispatch scheduling problem. With the intent to solve this problem, we decompose a dispatch scheduling problem into a master problem(MP) and several subproblems(SPs) using Benders decomposition. The MP solves a general optimal power flow(OPF) problem while the SPs inspect the feasibility of OPF solution under respective transmission line contingencies. If a dispatch scheduling solution given by the MP violates transmission security constraints, then additional constraints corresponding to the violations are imposed to the MP. Through this iterative process between the MP and SPs, we derive an optimal dispatch schedule incorporating the post-contingency corrective rescheduling. In addition, we consider interruptible loads as active control variables since the interruptible loads can participate as generators in competitive electricity markets. Numerical examples demonstrate the efficiency of the proposed algorithm.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• Journal of the Korean Society of Safety
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• v.10 no.3
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• pp.68-80
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• 1995

A series of parametric calculations have been performed in order to investigate the short-term and short-range plume and puff behavior of toxic gaseous and solid pollutant dispersion in an open atmosphere. The simulation is made by the use of the computer program developed by this laboratory, in which a control-volume based finite-difference method is used together with the SIMPLEC algorithm for the resolution of the pressure-velocity coupling appeared In Wavier-Stokes equation. The Reynolds stresses are solved by the standard two-equation k-$\varepsilon$ model modified for buoyancy together with the RNG(Renormalization Group) k-$\varepsilon$ model. The major parameters considered in this calculation are pollutant gas density and temperature, the relative velocity of pollutants to that of the surrounding atmospheric air, and particulate size and density together with the height released. The flow field is typically characterized by the formation of a strong recirculation region for the case of the low density gases such as $CH_4$ and air due to the strong buoyancy, while the flow is simply declining pattern toward the downstream ground for the case of heavy molecule like the $CH_2C1_2$and $CCl_4$, even for the high temperature, $200^{\circ}C$. The effect of gas temperature and velocity on the flow field together with the particle trajectory are presented and discussed in detail. In general, the results are physically acceptable and consistent.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.10
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• pp.89-96
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• 2008

The objective of this study is to establish the algorithm for contamination criterion map based on the recent weather condition. Present criterion was established by the study on the countermeasure of salt contamination for electrical equipment. It did not represent recent weather condition. Therefore it is necessary to develop a contamination criterion map for assessment of contamination in design areas in Korea. To develop contamination criterion map of seashore areas, we used relational numerical formula based on past measurement data with the amount of rainfall, geomorphic variables(elevation slope, land use). These results are expected to be used as a reference material for design distribution facilities in seashore areas.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.399-406
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• 2020

In this paper, we propose a time-varying proportional navigation guidance law that determines the proportional navigation gain in real-time according to the operating situation. When intercepting a target, an unidentified evasion strategy causes a loss of optimality. To compensate for this problem, proper proportional navigation gain is derived at every time step by solving an optimal control problem with the inferred evader's strategy. Recently, deep reinforcement learning algorithms are introduced to deal with complex optimal control problem efficiently. We adapt the actor-critic method to build a proportional navigation gain network and the network is trained by the Proximal Policy Optimization(PPO) algorithm to learn an evasion strategy of the target. Numerical experiments show the effectiveness and optimality of the proposed method.

• Journal of the Korean Institute of Navigation
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• v.15 no.3
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• pp.1-11
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• 1991

As increasing needs of marine transportation , world merchant fleet and ship's size were enlarged and it caused frequent disasters in human lives and natural environment. By the reason of the above, they started to establish the Vessel Traffic System (VTS) at the European coast in 1960' and most of advanced contries established and managed it to prevent the sea traffic accidents in these days. The concept of traffic control at sea can be divided into three types. First, the initial gathering of informations about ship's identity and movement etc.. Second, monitoring of the traffic flow and amendment of instructions. Third , organization and direction of ships by allocating routes and speeds. Where the goal of traffic control is safety of traffics and developing effectiveness of navigation channel, if traffic volume is less tan channel capacity then the above first or second level of control would be sufficient but if it is bigger than that , more positive policy of control should be adopted as same as third type of the above. In this paper where the strategy of VTS is focused on the control of traffic density to be spread equality, as possible , all over the navigation channels and also improvement of effectiveness , it suggests algorithm to assign the vessels to the channels with balanced traffic density , and other algorithms using D.P. to sequence the vessels assigned to one channel in optimum order which decreases the mean waiting time in sense of channel effectiveness with numerical examples.