• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1939-1951
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• 1994

This study introduces a new tool breakage detecting technology comprised of an unsupervised neural network combined with adaptive time series autoregressive(AR) model where parameters are estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(Recursive Least Square). Experiment indicates that AR parameters are good features for tool breakage, therefore it can be detected by tracking the evolution of the AR parameters during milling process. an ART 2(Adaptive Resonance Theory 2) neural network is used for clustering of tool states using these parameters and the network is capable of self organizing without supervised learning. This system operates successfully under the wide range of cutting conditions without a priori knowledge of the process, with fast monitoring time.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.491-501
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• 2006

We consider a multiple change point model with autoregressive conditional heteroscedasticity (ARCH). The model assumes that all or the part of the parameters in the ARCH equation change over time. The occurrence of the change points is modelled as the discrete time Markov process with unknown transition probabilities. The model is estimated by Markov chain Monte Carlo methods based on the approach of Chib (1998). Simulation is performed using a variant of perfect sampling algorithm to achieve the accuracy and efficiency. We apply the proposed model to the simulated data for verifying the usefulness of the model.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.211-213
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• 2005

In this paper, the frequency compensator for digital protective relay is introduced. Due to sudden appearance of generation-load or fault in power system, the frequency can deviate from its nominal value. The Orthogonal filter adopted to digital protective relay is exposed to the problem. Therefore, the frequency variation makes a difficult to protective function and power measurement in digital protective relay. The essential property of the proposed algorithm presented is its outstanding immunity to both signal orthogonal component magnitudes and DFT filter gain variations which ensures below 0.05Hz accuracy of estimation. Additionally, the proposed method has excellent characteristics with low signal sampling rate. Based on the frequency estimation, author design under frequency protection relay for generator and verifies its performance with several experimental tests.

• ETRI Journal
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• v.25 no.5
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• pp.345-355
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• 2003

In this paper, we propose a method for designing a class of M-channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop-band attenuation, which is also taken care of in the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.685-689
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• 2005

In this paper, we consider a robust output feedback model predictive controller(MPC) design for Wiener model. Nonlinearities that couldn't be represented in static nonlinearity block of Wiener model are regarded as uncertainties in linear block. An dynamic output feedback controller design method is presented for Wiener MPC. According to MPC algorithm, the control law is computed based on linear matrix inequality(LMI)at each sampling time by solving convex optimization. Also, a new parameter dependent Lyapunov function is proposed to get a less conservative condition. The results are illustrated with numerical example.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.105-110
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• 2001

A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paler describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1863-1866
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• 2003

In this study, respiratory motion is modeled by a 2-Dimensional linear expanding-shrinking movement. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimated, a reconstruction algorithm based on superposition method was used to removed the MRI artifact. For the purpose of estimating unknown motion parameters, we applied the spectrum shift method to find the respiratory fluctuation function, the x directional expansion coefficient and its center, and also we used the minimum energy method to find the y directional expansion coefficient and its center. The effectiveness of this presented method is shown by Computer simulations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.4
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• pp.317-326
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• 2008

The main purpose of the present study is to perform shape optimizations of transonic compressor blade in order to enhance its performance. In this study, the Latin hypercube sampling of design of experiments and the weighted average surrogate model with the help of a gradient based optimization algorithm are used within design space by the lower and upper limits of each design variable and for finding optimum designs, respectively. 3-D Reynolds-averaged Navier-Stokes solver is used to evaluate the objective functions of adiabatic efficiency and pressure ratio. Six variables from lean and airfoil thickness profile are selected as design variables. The results show that the adiabatic efficiency is enhanced by 1.43% by efficiency optimization while the pressure ratio is increased very small, and pressure ratio is increased by 0.24% by pressure ratio optimization.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.285-285
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• 2000

A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paper describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.443-446
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• 1997

HRV(heart rate variability) is the time series data of R-R interval time duration based on ECGs. Power spectral analysis of HRV has recently been used to define the activity of ANS(autonomic nervous system). In this study, 14 rats were divided into two groups, sympathectomy and vagotomy. During the experiments, ECGs of rats were collected three times at each experimental conditions or the duration of 5 minutes, where sampling frequency was set at 2KHz. After the application of the Berger's Serires algorithm to ECG raw data, power spectrum of HRV was obtained via FFT. Results showed that HF/LF were increased or the sympathectomy group and decreased or the vagotomy group. It implies that the variations in HF/LF components could be used or the ANS function classification.