• 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.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.2
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• pp.17-25
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• 2004

In this Paper, new data matrix structure and respective processing algorithm for digital holographic storage are Proposed. Data matrix consists of user data and reference grid which is used to compensate geometrical errors such as magnification, shift and rotation of stored information. Processing algorithm identifies the location of reference grid and extracts user data. As a result of experiment, raw BER in case of shit, rotation and magnification are 3.09${\times}$10$^{-18}$ , 6.14${\times}$10$^{-12}$ , 1.2${\times}$10$^{-7}$ , respectively.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.8
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• pp.705-713
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• 2014

In this paper, we propose a novel velocity ripple controller using phase compensation feedforward control. Velocity ripples result in many kinds of performance degradations in manufacturing machines, especially such as ultra-precision roll lathes. The generation of velocity ripple in constant velocity control comes from various causes, such as electrical torque ripples, mechanical worn out, inconsistent mass center, etc. Conventional researches about ripple is mainly for reducing torque ripple in actuator level, which is only one of reasons for velocity ripples, so in this study, we focus on eliminating velocity ripples in upper level controller using phase compensation feedforward controller. The proposed algorithm is composed of several modules, such as ripple extractor, phase adjuster and phase follower etc. The suggested algorithm can be easily extended, and it shows a superior performance in the experiments of ultra-precision roll lathes.

• ETRI Journal
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• v.31 no.4
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• pp.408-418
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• 2009

Adopting an encryption function in voice over Wi-Fi service incurs problems such as additional power consumption and degradation of communication quality. To overcome these problems, a partial encryption (PE) algorithm for compressed speech was recently introduced. However, from the security point of view, the partial encryption sets (PESs) of the conventional PE algorithm still have much room for improvement. This paper proposes a new selection method for finding a smaller PES while maintaining the security level of encrypted speech. The proposed PES selection method employs the perceptual evaluation of the speech quality (PESQ) algorithm to objectively measure the distortion of speech. The proposed method is applied to the ITU-T G.729 speech codec, and content protection capability is verified by a range of tests and a reconstruction attack. The experimental results show that encrypting only 20% of the compressed bitstream is sufficient to effectively hide the entire content of speech.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.118-129
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• 2011

In this paper, we suggest a new camera capturing and synthesizing algorithm with the multi-captured left and right images for the better comfortable feeling of 3D depth and also propose 3D image capturing hardware system based on the this new algorithm. We also suggest the simple control algorithm for the calibration of camera capture system with zooming function based on a performance index measure which is used as feedback information for the stabilization of focusing control problem. We also comment on the theoretical mapping theory concerning projection under the assumption that human is sitting 50cm in front of and watching the 3D LCD screen for the captured image based on the modeling of pinhole Camera. We choose 9 segmentations and propose the method to find optimal alignment and focusing based on the measure of alignment and sharpness and propose the synthesizing fusion with the optimized 9 segmentation images for the best 3D depth feeling.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.185-190
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• 2007

In this study, we developed the 2.5D EM modeling and inversion algorithm for cross-hole source and receiver geometry. Considering the cross-hole environment, we use a VMD (vertical magnetic dipole) as a source and vertical magnetic fields as a measuring data. Developed inversion algorithm is tested for the isolated block model which has a conductive and a resistivity anomaly respectively. For the conductive anomaly, its size and resistivity are inverted well on the inversion results, while for the resistive anomaly, the location of anomalous block is shown on the inverted section, but its values are far from the exact value. Furthermore, artificial conductive anomalies are shown around the resistive anomalous zone. If we consider the inversion artifact shown in the test inversion of restive block, it is almost impossible to image the resistive zone. However, the main target of EM tomography in the engineering problem is conductive target such as fault zone, and contaminated zone etc., EM tomography algorithm can be used for detecting the anomalous zone.

• ETRI Journal
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• v.28 no.3
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• pp.320-328
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• 2006

Using biometrics to verify a person's identity has several advantages over the present practice of personal identification numbers (PINs) and passwords. To gain maximum security in a verification system using biometrics, the computation of the verification as well as the storing of the biometric pattern has to take place in a smart card. However, there is an open issue of integrating biometrics into a smart card because of its limited resources (processing power and memory space). In this paper, we propose a speaker verification algorithm using a support vector machine (SVM) with a very few features, and implemented it on a 32-bit smart card. The proposed algorithm can reduce the required memory space by a factor of more than 100 and can be executed in real-time. Also, we propose a hardware design for the algorithm on a field-programmable gate array (FPGA)-based platform. Based on the experimental results, our SVM solution can provide superior performance over typical speaker verification solutions. Furthermore, our FPGA-based solution can achieve a speed-up of 50 times over a software-based solution.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.112-117
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• 2007

In this paper, we focus on the total transmission power minimization problem for downlink beamforming multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems while ensuring each user's QoS requirement. Although the linear integer programming (LIP) solution we formulate provides the performance upper bound of the margin adaptive (MA) optimization problem, it is hard to be implemented in practice due to its high computational complexity. By regarding each user's equivalent channel gain as approximate independent values and using iterative descent method, we present a heuristic MA resource allocation algorithm. Simulation results show that the proposed algorithm efficiently converges to the local optimum, which is very close to the performance of the optimal LIP solution. Compared with existing space division multiple access (SDMA) OFDM systems with or without adaptive resource allocation, the proposed algorithm achieves significant performance improvement by exploiting the frequency diversity and multi-user diversity in downlink multiple-input single-output (MISO) OFDM systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.38-44
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• 2016

In this paper, Author of this article presents a system to ensure the safety of residents in case the residents occurs an fall situation. Author of this article use weighted difference image and motion vector. Proposed system suggested the fall detection algorithm using weighted difference image and motion vector. Fall detection algorithm showed a success rate of 85% ~ 97.1% through 150 experiments. Proposed algorithm showed a litter higher or similar success rate than the existing camera based system.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.431-434
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• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.