• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.539-542
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• 2003

A motor is the workhorse of our industry. The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. Different internal motor faults (e.g., inter-turn short circuits, broken bearings, broken rotor bars) along with external motor faults (e.g., phase failure, mechanical overload, blocked rotor) are expected to happen sooner or later. This paper introduces the fault detection technique of induction motors based upon the stator current. The fault motors have rotor bar broken or rotor unbalance defect, respectively. The stator currents are measured by the current meters and stored by the time domain. The time domain is not suitable to represent the current signals, so the frequency domain is applied to display the signals. The Fourier Transformer is used for the conversion of the signal. After the conversion of the signals, the features of the signals have to be extracted by the signal processing methods like a wavelet analysis, a spectrum analysis, etc. The discovered features are entered to the pattern classification model such as a neural network model, a polynomial neural network, a fuzzy inference model, etc. This paper describes the fault detection results that use wavelet decomposition. The wavelet analysis is very useful method for the time and frequency domain each. Also it is powerful method to detect the features in the signals.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.587-590
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• 2005

In this paper, the PWM inverter-motor drive system including sensor is controlled through the network. The algorithm to compensate for the time delay of ac current and ac voltage sensors due to the network is proposed. The delay time of sensors is kept nearly constant, using the synchronous signal and timers. The error between the real and estimated ac signals can be reduced by using two slopes for estimating the value of at signals. The proposed algorithms are verified with the simulation studies and experiments.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.430-437
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• 2018

Ultrasonic attenuation is an important parameter in Quantitative Ultrasound and many algorithms have been proposed to improve estimation accuracy and repeatability for multiple independent estimates. In this work, we propose an improved algorithm for estimating ultrasonic attenuation utilizing the optimal frequency compounding technique based on stochastic noise model. We formulate mathematical compounding equations in the AWGN channel model and solve optimization problems to maximize the signal-to-noise ratio for multiple frequency components. Individual estimates are calculated by the reference phantom method which provides very stable results in uniformly attenuating regions. We also propose the guideline to select frequency ranges of reflected RF signals. Simulation results using numerical phantoms show that the proposed optimal frequency compounding method provides improved accuracy while minimizing estimation bias. The estimation variance is reduced by only 16% for the un-compounding case, whereas it is reduced by 68% for the uniformly compounding case. The frequency range corresponding to the half-power for reflected signals also provides robust and efficient estimation performance.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2167-2169
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• 2003

The LQG regulator presented in this dissertation is designed to improve system stability with the structure in which Kalman Filters and LQ regulator are inter-connected to avoid disturbances on the system. For the sake of performance evaluation of the LQG regulator in this dissertation, the regulator is put in use for the speed control of DC Servo Motors without speed sensors on them to realize speed control without sensors by estimating uncertain speed with its state signals and to construct an optimal controller using the LQG regulator. Furthermore, state estimation process with white noise entered onto the systems is been experimented through a series of simulation. As a consequence, the process of estimating speed signals out of the signals with white noise inputs is confirmed using Kalman Filter.

• KIEE International Transactions on Electrophysics and Applications
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• v.11C no.2
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• pp.6-11
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• 2001

Abstract- In this paper, a new Partial Discharge (PD) detection using Pockels cell was proposed and considerable apparent chaotic characteristics were discussed. For this purpose, PD was generated from needle-plane electrode in air and detecte by optical measuring system using Pockels cell, based on Mach-Zehner interferometer, consisting of He-Ne laser, single mode optical fiber, 50/50 beam splitter and photo detector. In addition, the presence of chaos of the PD signals has been investigated by examining their means of qualitative and quantitative information. For the former, return map and 3-dimensional strange attractor have been drawn in order to investigate the presence of chaotic characteristics relevant to PD signals, detected through CT and Peckels sensor respectively, in the normalized time series. The presence of strange attractor indicates the existence of fractal structures in it's phase space. For the latter, several dimension values of strange attractor were verified sequentially. Throughout this paper, it is likely that the chaotic characteristics regarding the PD signals under air are verified.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1699-1701
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• 2010

The Active Noise Cancelling(ANC) headphone is now becoming commercially available. But it reduces not only noise but also information signals such as speech or some signals including audible information in particular situation. In this paper, we propose an ANC headphone using adaptive beam-forming techniques which cancels signals except the headphone wearer's look direction signal. It enables workers working in noisy condition to talk with their coworkers. Computer simulation is performed to show the effectiveness of a proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.332-334
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• 2006

In this paper, we present an equalization scheme for 8-VSB signals for the ATSC DTV system. We propose a complex feedback filter and complex feedback sample generator for DFE to equalize 8-VSB signals in order to efficiently remove multipath distortions causing leakages from the qudrature component. We show that the proposed structure outperforms the conventional DFE used for the digital VSB which uses a real-valued feedback filter with real-valued decisions.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2000.11a
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• pp.231-234
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• 2000

The corona in oil, the surface discharge in oil, the void discharge which could be in a transformer were imitated by using three electrodes with different shapes and the frequency bands of each ultrasonic signal were measured. After emitting artificial noises toward the transformer, only ultrasonic signals were extracted by frequency filtering, from the ultrasonic signals with noises at partial discharge. As a result, it was confirmed that the ultrasonic signals due to the corona in oil, the surface discharge in oil, the void discharge could be distinguished from the noises.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.362-366
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• 1998

This paper proposes a fast H$\sub$$\infty$/ gain scheduled controller that stabilizes the uncertain nonlinear system with exogenous signals. The controller is constructed at a distinct and fixed value of exogenous signals using H$\sub$$\infty$/ syn-thesis methodology. Then the constructed controller set is switched for the wide range of variation of exogenous signals. Using the derivative gain, the number of constructed and engaged controllers for the fast varying exogenous signal is reduced.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.291-296
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• 2014

Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of weak stationarity. The purpose of this study is to analyze the accuracy of the Run-test, modified Run-test, RA(reverse arrangement)-test, and modified RA-test for assessing surface EMG signal stationarity. Six stationary and three non-stationary signals were simulated by using sine wave, AR(autoregressive) modeling, and real surface EMG. The simulated signals were tested for stationarity using nine different methods of Run-test and RA-test. The results showed that the modified Run-test method2 (mRT2) classified exactly the surface EMG signals by stationarity with 100% accuracy. This finding indicates that the mRT2 may be the best way for assessing stationarity in surface EMG signals.