• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2001-2005
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• 2008

This paper presents a design of a simulation apparatus to evaluate an operational control algorithm for the PRT system. PRT systems require very short headways to increase the line capacity and a very reliable vehicle control algorithm for avoidance of the impact between vehicles. Therefore, it can be said that the development of an reliable operational control algorithm for the PRT systems is much more important than that of the hardware configurations. In this paper an apparatus is proposed which is composed of virtual vehicles, a central control system, a man-machine interface and monitoring device, making it possible for the designed operational control algorithm to be implemented and tested. For the test of the proposed apparatus a test operational control algorithm is designed and the experimental results show the effectiveness of the proposed simulation apparatus for test and evaluation of the PRT operational control algorithms.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.432-438
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• 2010

In this paper, we propose a system which can perceive status of semiconductor equipment and evaluate its performance. The proposed system acquires the information such acceleration, pressure, temperature and gas sensors in the surrounding semiconductor equipment. After acquiring information, it is sent to server through multi hop transmission. The transmitted data generates 3 steps alarm using context-aware algorithm of unit or multiple event. From the experiment's result of the proposed system, we confirm that the reliability and efficiency of information is more improved about 80% than a system that doesn't use context-aware algorithm. Moreover, this system can be effective status monitoring of semiconductor equipment because lots of client nodes acquire surrounding information.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.852-856
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• 2004

An induction motor is one of the most popular electrical apparatuses owing to its simple structure and robust construction. Parameter identification of the induction motor has long been researched either for a vector control technique or fault detection. Since vector control is a well-established technique for induction motor control, this paper concentrates on successive identification of physical parameters with on-load data for the purpose of condition monitoring and/or fault detection. For extracting six physical parameters from the on-load data in the framework of the induction motor state equation, unmeasured initial state values and profiles of load torque have to be estimated as well. However, the analytic optimization methods in general fail to estimate these auxiliary but significant parameters owing to the difficulty of obtaining their gradient information. In this paper, the univariate dynamic encoding algorithm for searches (uDEAS) newly developed is applied to the identification of whole unknown parameters in the mathematical equations of an induction motor with normal operating data. Profiles of identified parameters appear to be reasonable and therefore the proposed approach is available for fault diagnosis of induction motors by monitoring physical parameters.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.471-483
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• 2012

In this paper, the structural health monitoring (SHM) benchmark problem of the Canton tower is studied. Based on the field monitoring data from the 20 accelerometers deployed on the tower, some modal frequencies and mode shapes at measured degrees of freedom of the tower are identified. Then, these identified incomplete modal data are used to update the reduced finite element (FE) model of the tower by a novel algorithm. The proposed algorithm avoids the problem of subjective selection of updated parameters and directly updates model stiffness matrix without model reduction or modal expansion approach. Only the eigenvalues and eigenvectors of the normal finite element models corresponding to the measured modes are needed in the computation procedures. The updated model not only possesses the measured modal frequencies and mode shapes but also preserves the modal frequencies and modes shapes in their normal values for the unobserved modes. Updating results including the natural frequencies and mode shapes are compared with the experimental ones to evaluate the proposed algorithm. Also, dynamic responses estimated from the updated FE model using remote senor locations are compared with the measurement ones to validate the convergence of the updated model.

• Journal of Astronomy and Space Sciences
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• v.34 no.1
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• pp.7-17
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• 2017

In South Korea, there are about 80 Global Positioning System (GPS) monitoring stations providing total electron content (TEC) every 10 min, which can be accessed through Korea Astronomy and Space Science Institute (KASI) for scientific use. We applied the computerized ionospheric tomography (CIT) algorithm to the TEC dataset from this GPS network for monitoring the regional ionosphere over South Korea. The algorithm utilizes multiplicative algebraic reconstruction technique (MART) with an initial condition of the latest International Reference Ionosphere-2016 model (IRI-2016). In order to reduce the number of unknown variables, the vertical profiles of electron density are expressed with a linear combination of empirical orthonormal functions (EOFs) that were derived from the IRI empirical profiles. Although the number of receiver sites is much smaller than that of Japan, the CIT algorithm yielded reasonable structure of the ionosphere over South Korea. We verified the CIT results with NmF2 from ionosondes in Icheon and Jeju and also with GPS TEC at the center of South Korea. In addition, the total time required for CIT calculation was only about 5 min, enabling the exploration of the vertical ionospheric structure in near real time.

• Journal of Welding and Joining
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• v.16 no.5
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• pp.76-85
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• 1998

The resistance spot welding process has been used for joining the sheet metal in automotive engineering. In the resistance spot welding, the weld quality is very important, because the quality of weld is one of the most important factors to the automobile quality. The size of he molten nugget has been utilized to estimate the weld quality. However, it is not easy to find the weld defects. For weldability estimation, we have to use the nondestructive method such as X-ray or ultrasonic inspection. But these kinds of approaches are not suitable for detecting the defects in real time. The purpose of this study is to develop the real time monitoring of the weld quality in the resistance spot welding. Obtained data were used to estimate weldability using fuzzy algorithm. It is sound that this monitoring and estimation system can be useful to improve the weld quality in the resistance spot welding process and it is possible to estimate the weldability in real time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.173-179
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• 2012

Recently, the requirements of large-dynamic management systems are increasing in multi-PC convergence environment because such system are out. In this research, it has been studied that the regression algorithm was applied instantly for abnormal state and the priority threshold process module was implemented. The system was optimized and become efficiently through the software design and implementation for multi-PC management. As a result, it has been possible for least person and system to manage a lot of requirements.

• Journal of the Korea institute for structural maintenance and inspection
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• v.1 no.2
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• pp.87-94
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• 1997

This research aims to develop an algorithm of optimal transducer placement using Kinetic Energy of the structural system. The structural vibration response-based health monitoring is considered one of the best for the system which requires a long-term, continuous monitoring. In its experimental modal testing, however, it is difficult to decide on the measurement locations and their number, especially for complex structures, which have a major influence on the quality of the results. In order to minimize the number of sensing operations and optimize the transducer location while maximizing the accuracy of results, this paper discusses about an optimum transducer placement criterion suitable for the identification of structural damage. As a criterion algorithm, it proposes the Kinetic Energy Optimization Technique (EOT), and then addresses the numerical issues which are subsequently applicable to actual experiment where a bridge model is used. By using the experimental data, it compares the EOT with the EIM (Effective Independence Method) which is generally used to optimize the transducer placement for the damage identification and control purposes. The comparison conclusively shows that the EOT algorithm proposed in this paper is preferable when a structure is to be instrumented with fewer sensors.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.309-315
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• 2016

The node mobility in the wireless mobile network environment increases the energy consumption. This paper proposes a CNMA (cluster-based node management algorithm) to reduce the energy consumption caused by node mobility, and to prolong the life cycle for cluster member nodes. The proposed CNMA traces the mobility for nodes between cluster header and member, and it analyses the energy capacity as monitoring periodically their relationship. So, it makes a division and merges by analysing the state transition for nodes. This paper is to reduce the energy consumption due to the node mobility. The simulation results show that the proposed CNMA can efficiently control the energy consumption caused by mobility, and it can improve the energy cycle.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.