• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.7
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• pp.281-289
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• 2006

Advanced controllers among Flexible AC Transmission System(FACTS) devices employ self-commutated switching converters, VSI (Voltage Sourced Inverters), as the synchronous voltage source. Such controllers are SSSC (Static Synchronous Series Compensator), STATCOM (Static Synchronous Compensator) and UPFC (Unified Power Flow Controller). UPFC is series-shunt combined controller. Its series and shunt inverters can be modeled as SSSC and STATCOM but the dependant relation between the inverters is very complex. For that reason, the complexity makes it difficult to develop the UPFC model by simply combining the SSSC and STATOM models when we apply the model for conventional power system dynamic simulation algorithm. Therefore, we need each relevant models of VSI type FACTS devices for power system analysis. This paper proposes a modeling approach which can be applied to modeling of VSI type FACTS devices. The proposed method using Newton-type current injection method can be used to make UPFC, SSSC, and STATCOM models. The proposed models are used for 2-area test system simulation, and the results verify their effectiveness.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.191-196
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• 2002

The paper presents a numerical and experimental investigation on dynamic behaviors of a towed low tension cable. In the numerical study, an implicit finite difference algorithm is employed for three-dimensional cable equations. Fluid and geometric non-linearity and bending stiffness are considered and solved by Newton-Raphson iteration. Block tri-diagonal matrix method is applied for the fast calculation of the huge size of matrices. In order to verify the numerical results and to see real physical phenomena, an experiment is carried out for a 6m cable in a deep and long towing tank. The cable is towed in two different ways; one is towed at a constant speed and the other is towed at a constant speed with top end horizontal oscillations. Cable tension and shear forces are measured at the top end. Numerical and experimental results are compared with good agreements in most cases but with some differences in a few cases. The differences are due to drag coefficients caused by vortex shedding. In the numerical modeling, non-uniform element length needs to be employed to cope with the sharp variation of tension and shear forces at near top end.

• Smart Structures and Systems
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• v.20 no.6
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• pp.669-682
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• 2017

The normalised version of bispectrum, the so-called bicoherence, has often proved a reliable method of damage detection on engineering applications. Indeed, higher-order spectral analysis (HOSA) has the advantage of being able to detect non-linearity in the structural dynamic response while being insensitive to ambient vibrations. Skewness in the response may be easily spotted and related to damage conditions, as the majority of common faults and cracks shows bilinear effects. The present study tries to extend the application of HOSA to damage localisation, resorting to a neural network based classification algorithm. In order to validate the approach, a non-linear finite element model of a 4-meters-long cantilever beam has been built. This model could be seen as a first generic concept of more complex structural systems, such as aircraft wings, wind turbine blades, etc. The main aim of the study is to train a Neural Network (NN) able to classify different damage locations, when fed with bispectra. These are computed using the dynamic response of the FE nonlinear model to random noise excitation.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.209-219
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• 2010

In this paper, a novel dynamic available transfer capability (DATC) has been computed for real time applications using three different intelligent techniques viz. i) back propagation algorithm (BPA), ii) radial basis function (RBF), and iii) adaptive neuro fuzzy inference system (ANFIS) for the first time. The conventional method of DATC is tedious and time consuming. DATC is concerned with calculating the maximum increase in point to point transfer such that the transient response remains stable and viable. The ATC information is to be continuously updated in real time and made available to market participants through an internet based Open Access Same time Information System (OASIS). The independent system operator (ISO) evaluates the transaction in real time on the basis of DATC information. The dynamic contingency screening method [1] has been utilized and critical contingencies are selected for the computation of DATC using the energy function based potential energy boundary surface (PEBS) method. The PEBS based DATC has been utilized to generate patterns for the intelligent techniques. The three different intelligent methods are tested on New England 68-bus 16 machine and 39-bus 10 machine systems and results are compared with the conventional PEBS method.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.371-384
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• 2012

This study proposes a multi-level data analysis approach to identify both superficial and latent relationships among variables in the data set obtained from a vocational rehabilitation (VR) services program of people with significant disabilities. At the first layer, data mining and statistical predictive models are used to extract the superficial relationships between dependent and independent variables. To supplement the findings and relationships from the analysis at the first layer, association rule mining algorithms at the second layer are employed to extract additional sets of interesting associative relationships among variables. Finally, nonlinear nonparametric canonical correlation analysis (NLCCA) along with clustering algorithm is employed to identify latent nonlinear relationships. Experimental outputs validate the usefulness of the proposed approach. In particular, the identified latent relationship indicates that disability types (i.e., physical and mental) and severity (i.e., severe, most severe, not severe) have a significant impact on the levels of self-esteem and self-confidence of people with disabilities. The identified superficial and latent relationships can be used to train education program designers and policy developers to maximize the outcomes of VR training programs.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2525-2532
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• 2009

In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.

• Journal of Communications and Networks
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• v.13 no.5
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• pp.536-543
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• 2011

The heterogeneous postal delivery model assumes that each intermediate node in the multicasting tree incurs a constant switching time for each message that is sent. We have proposed a new model where we assume a more generalized switching time at intermediate nodes. In our model, a child node v of a parent u has a switching delay vector, where the ith element of the vector indicates the switching delay incurred by u for sending the message to v after sending the message to i-1 other children of u. Given a multicast tree and switching delay vectors at each non-root node 5 in the tree, we provide an O(n$^{\frac{5}{2}}$) optimal algorithm that will decide the order in which the internal (non-leaf) nodes have to send the multicast message to its children in order to minimize the maximum end-to-end delay due to multicasting. We also show an important lower bound result that optimal multicast switching delay problem is as hard as min-max matching problem on weighted bipartite graphs and hence O(n$^{\frac{5}{2}}$) running time is tight.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1262-1264
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• 2003

The author Present a modified multiloop algorithm including feedforward for controlling a 45kW step down chopper in the power supply of Maglev. The control law for the duty cycle consists of three terms. The first is the feedforward term which compensates for variations in the input voltage. The second term consists of the difference between the slowly moving inductor current and output current. The third term consists of proportional and integral terms involving the perturbation in the output voltage. This perturvation is derived by subtracting the desired output voltage from the actual output voltage. The proportional and integral action stabilizes the system and minimizes output voltage error. To verify the validity of the proposed multiloop controller, simulation study was tried using Matlab/sirnulink.