• Smart Structures and Systems
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• v.23 no.6
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• pp.653-667
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• 2019

Using cross-ties to connect cables together when forming a cable network is regarded as an efficient method of mitigating cable vibrations. Cross-ties have been extended and fixed on bridge decks or towers in some engineering applications. However, the dynamics of this kind of system need to be further studied, and the effects of extending cross-links to bridge decks/towers on the modal response of the system should be assessed in detail. In this paper, a system of two cables connected by an inter-supported cross-link with another lower cross-link extended to the ground is proposed and analyzed. The characteristic equation of the system is derived, and some limiting solutions in closed form of the system are derived. Roots of cable system with special configurations are also discussed, attention being given to the case when the two cables are identical. A predictable mode behavior was found when the stiffness of inter-connection cross-link and the cross-link extended to the ground were the same. The vector of mode energy distribution and the degree of mode localization index are proposed so as to distinguish global and local modes. The change of mode behaviors is further discussed in the case when the two cables are not identical. Effects of cross-link stiffness, cross-link location, mass-tension ratio, cable length ratio and frequency ratio on $1^{st}$ mode frequency and mode shape are addressed.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.789-792
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• 2004

In various fields as web mining, bioinformatics, statistical data analysis, and so forth, very diversely missing values are found. These values make training data to be sparse. Largely, the missing values are replaced by predicted values using mean and mode. We can used the advanced missing value imputation methods as conditional mean, tree method, and Markov Chain Monte Carlo algorithm. But general imputation models have the property that their predictive accuracy is decreased according to increase the ratio of missing in training data. Moreover the number of available imputations is limited by increasing missing ratio. To settle this problem, we proposed statistical learning theory to preprocess for missing values. Our statistical learning theory is the support vector regression by Vapnik. The proposed method can be applied to sparsely training data. We verified the performance of our model using the data sets from UCI machine learning repository.

• Steel and Composite Structures
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• v.25 no.4
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• pp.485-496
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• 2017

In this paper, damage detection has been introduced as an optimization problem and a two-step method has been proposed that can detect the location and severity of damage in truss structures precisely and reduce the volume of computations considerably. In the first step, using the residual force vector concept, the suspected damaged members are detected which will result in a reduction in the number of variables and hence a decrease in the search space dimensions. In the second step, the precise location and severity of damage in the members are identified using the genetic algorithm and the results of the first step. Considering the reduced search space, the algorithm can find the optimal points (i.e. the solution for the damage detection problem) with less computation cost. In this step, the Efficient Correlation Based Index (ECBI), that considers the structure's first few frequencies in both damaged and healthy states, is used as the objective function and some examples have been provided to check the efficiency of the proposed method; results have shown that the method is innovatively capable of detecting damage in truss structures.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• Journal of electromagnetic engineering and science
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• v.3 no.2
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• pp.126-132
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• 2003

In this paper, a coupled-line type waveguide bandpass filter is newly proposed. The proposed bandpass filter configuration consists of magnetically coupled waveguide cavities. In order to show the background of the proposed waveguide bandpass filter, the general coupled line TEM bandpass filter theory, which means the coupled line filter with arbitrary coupled line length and impedance level, will be briefly introduced. Calculations for the even- and odd-mode wave impedance of a coupled line waveguide structure are achieved based on the normalized impedance concept for a broad-side coupled waveguides by using vector finite element method(VFEM) calculation. Measured result of an implemented coupled-line type waveguide filter is presented.

• ETRI Journal
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• v.29 no.3
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• pp.390-392
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• 2007

In this paper, we propose a new error concealment (EC) method using inter-layer correlation for scalable video coding. In the proposed method, the auxiliary motion vector (MV) and the auxiliary mode number (MN) of intra prediction are interleaved into the bitstream to recover the corrupted frame. In order to reduce the bit rate, the proposed method encodes the difference between the original and the predicted values of the MV and MN instead of the original values. Experimental results show that the proposed EC outperforms the conventional EC by 2.8 dB to 6.7 dB.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.616-621
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• 2004

This paper investigated the speed sensorless indirect vector control of a two-phase induction motor to implement adjustable-speed drive for low-power applications. The sliding mode observer estimates rotor speed. The convergence of the nonlinear time-varying observer along with the asymptotic stability of the controller was analyzed. To define the control action which maintains the motion on the sliding manifold, an 'equivalent control' concept was used. It was simulated and implemented on a sensorless indirect vector drive for 150W two-phase induction motor. The simulation and experimental results demonstrated effectiveness of the estimation method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.507-510
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• 1998

In this paper, a novel test method is proposed to detect hard and soft fault in CMOS operational amplifiers. Proposed test method mark use of the offset character, which is one of the op-amps characteristics. During the test mode, CUT is implemented to unit gain op-amps with feedback loop. When the input is grounded, a good circuit has a small offset voltage, but a faulty circuit has a large offset voltage exceeding predefined range of tolerance. Using the proposed method, no test vector is required to be applied. Therefore the test vector generation problem is eliminated and the test time is reduced. The accuracy and effectiveness of the method is verified through HSPICE simulation.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2088-2090
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• 1997

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification. The proposed adaptive algorithm for rotor resistance estimation in the synchronous reference frame is applied by sliding mode current controller satisfing persistent excitation(PE) condition. Adaptive flux observer is here used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verify the validity of the proposed algorithm.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.