• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.399-402
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• 1996

The electrodynamic loudspeakers should have a wide dynamic range to reproduce various sound levels. When the input signal is small, the radiated sound from the loudspeaker is not so much distorted. However, for large input signal with low frequency component the radiated sound is significantly distorted due to the nonlinearities of the loudspeaker. The suspension, damping, and magnetic flux of loudspeaker are the main sources of the nonlinearity. Such electromechanical parameters related to harmonic distortion have been represented by a polynomial model for diaphragm displacement, while each of the polynomial coefficient is evaluated by using the principle of harmonic balance experimentally. Based on the polynomial model, we designed a compensator for nonlinear harmonic distortion of direct radiator loudspeaker. Than observer is used to estimate the displacement of the loudspeaker diaphragm, which is rather difficult to measure directly in the conventional setting. The usefulness of the designed compensator is demonstrated by numerical simulations. Simulation results show about 30db decrease at the second and third higher harmonic distortions. We carry out an experiment on speaker to verify designed controller and nonlinear observer.

• The KSFM Journal of Fluid Machinery
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• v.10 no.3 s.42
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• pp.9-16
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• 2007

Deterioration of surface of turbomachinery blades occurs in course of time due to many factors and hence reduces the performance of the machine. In this paper, the effects of surface roughness of transonic axial compressor blade on performance are studied considering a reference blade and a shape distorted (optimized) blade. Optimal blade is designed considering sweep and lean. Baldwin-Lomax turbulence model is used for flow field analysis and Cebeci-Smith roughness model is formulated for roughness modeling. It is found that, as the surface roughness increases, adiabatic efficiency, total temperature ratio and total pressure ratio decrease while Mach number increases. Performance deterioration is more severe in case of distorted blade as compared to reference blade.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.268-269
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• 2017

This paper presents an improved current control strategy for a three-phase grid-connected inverter under distorted grid conditions. Distorted grid condition is undesirable due to negative effects such as power losses and heating problem in electrical equipments. To enhance the power quality of distributed generation systems under such a condition, a modulated finite control set - model predictive control (MFCS-MPC) scheme will be proposed, in which the optimal switching signals of inverter are chosen by online basis using the principle of current error minimization. In addition, the moving average filter (MAF) is used to improve the phase-lock loop in order to obtain the harmonic-free reference currents on the stationary frame. The usefulness of the proposed MFCS-MPC method is proved by the comparative simulation results under different operating conditions.

• Proceedings of the Acoustical Society of Korea Conference
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• 1997.06a
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• pp.27-34
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• 1997

In this study , we tried to test the classification performance of a neural netow and thereby to examine its applicability to the signals distorted by a shallow water einvironment . We conducted an acoustic experiment iin a shallow sea near Pohang, Korea in which water depth is about 60m. The signals, on which the network has been tested, is ilinear frequency modulated ones centered on one of the frequencies, 200, 400, 600 and 800 Hz, each being swept up or down with bandwidth 100Hz. we considered two transforms, STFT(short-time Fourier transform) and PWVD (pseudo Wigner-Ville distribution), form which power spectra were derived. The training signals were simulated using an acoutic model based on the Fourier synthesis scheme. When the network has been trained on the measured signals of center frequency 600Hz,it gave a little better results than that trained onthe simulated . With the center frequencies varied, the overall performance reached over 90% except one case of center frequency 800Hz. With the feature extraction techniques(STFT and PWVD) varied,the network showed performance comparable to each other . In conclusion , the signals which have been simulated with water depth were successully applied to training a neural network, and the trained network performed well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• Journal of Power Electronics
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• v.17 no.1
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• pp.262-271
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• 2017

This paper studies the performances of five typical Phase-locked Loops (PLLs) for distorted and unbalanced grid, which are the Decoupled Double Synchronous Reference Frame PLL (DDSRF-PLL), Double Second-Order Generalized Integrator PLL (DSOGI-PLL), Double Second-Order Generalized Integrator Frequency-Lock Loop (DSOGI-FLL), Double Inverse Park Transformation PLL (DIPT-PLL) and Complex Coefficient Filter based PLL (CCF-PLL). Firstly, the principles of each method are meticulously analyzed and their unified small-signal models are proposed to reveal their interior relations and design control parameters. Then the performances are compared by simulations and experiments to investigate their dynamic and steady-state performances under the conditions of a grid voltage with a negative sequence component, a voltage drop and a frequency step. Finally, the merits and drawbacks of each PLL are given. The compared results provide a guide for the application of current control, low voltage ride through (LVRT), and unintentional islanding detection.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.54-65
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• 1998

This study attempts to test the classifying performance of a neural network and thereby examine its applicability to the signals distorted in a shallow water environment. Linear frequency modulated(LFM) signals are simulated by using an acoustic model and also measured through sea experiment. The network is constructed to have three layers and trained on both data sets. To get normalized power spectra as feature vectors, the study considers the three transforms : shot-time Fourier transform (STFT), wavelet transform (WT) and pseudo Wigner-Ville distribution (PWVD). After trained on the simulated signals over water depth, the network gives over 95% performance with the signal to noise ratio (SNR) being up to-10 dB. Among the transforms, the PWVD presents the best performance particularly in a highly noisy condition. The network performs worse with the summer sound speed profile than with the winter profile. It is also expected to present much different performance by the variation of bottom property. When the network is trained on the measured signals, it gives a little better results than that trained on the simulated data. In conclusion, the simulated signals are successfully applied to training a network, and the trained network performs well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• English & American cultural studies
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• v.9 no.1
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• pp.27-50
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• 2009

Henry James tries to describe minutely in The Wings of the Dove the process in which a bad faith grows, is practiced in one's self, and spreads to a society. Through this fictional specificity, he embodies an analogy between a bad faith and social role-playing. That is, he shows, through the main characters such as Milly Theale and Merton Densher, how self interacts with the other and a society. In this interaction, there is some essential element, namely, an organic relationship between a self identity and a social role-model, which James describes very meticulously. Therefore, the characters are depicted as seeking to define self identity and eventually distorting it. Thus, The Wings of the Dove can be seen as a tragedy in which the characters who have this wrongly distorted self identity come to experience its effects. The distorted self identity appears to function as a social role. Milly distorts her true self identity by internalizing a dove-image for it. This results in a bad faith. Moreover, the American girl Milly utilizes it as a convenient social role-model which makes it easy for her to interact and engage with the others in the European society. Merton also evades adventurous and painful self-reflection and self-criticism by sticking to the mannerisms of gentlemanship and imitates the sublimity which Milly shows him. Thus, Milly and Merton clearly omit self-inspection and self-inquiry for the contact between a free self and a society, which is essential to obtain social objectivity, namely, intersubjectivity.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.8 no.1
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• pp.22-33
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• 1997

The objective of this study is to understand disordered parent-child relationships of Reactive Attachment Disorder(RAD) systematically through the mother’ internal working model of child. In this study, RAD mothers’internal representations of the child were compared with mothers’of control group and association between mothers’ representation classifications and children’ attachment classifications was examined. Also individual differences in mother-child interaction by mothers’representation classifications was observed. The subjects of this study were 40 2-5 year-old children and their mothers, 20 attachment disordered dyads and 20 normal dyads of control group. Mothers were interviewed using the Working Model of the Child(Zeanah, Benoit & Barton 1986) to classify internal representations of child. Children’ attachment patterns were assessed by the Strange Situation Procedure. For observation of motherchild interaction, Each dyad was seen in DPICS devised by Eyberg and Robinson(1983). The results of the study were as follows：1) Among RAD group, 55% of mothers were classified as disengaged and 45% classified as distorted, while all mothers of control group were classified as balanced. In rating scales, there were significant differences in all 3 representation classifications in Intensity of involvement and Coherence. In Intensity of involvement disengaged representations had the lowest score and distorted representations had the lowest score in Coherence. 2) Mothers’representation classifications were related to children’ attachment classifications. All mothers of control group whose children were classified as secure were classified as balanced. Among RAD’ mothers, by contrast, 82% of mothers classified as disengaged had children classified as anxious-avoidant, 56% of mothers classified as distorted had children classified as disorganized / disoriented and 33% of mothers classified as distorted had children classified as anxious-resistant. 3) There were individual differences in mother-child interactions by mothers’representation classifications. In the child-centered play, mothers classified as disengaged used discriptive statement, reflective statement and discriptive-reflective question less than balanced mothers. Mothers classified as distorted used direct command and indirect command more than balanced mothers. In the clean-up task, mothers classified as disengaged and distorted used direct command and indirect command more than balanced mothers. The results of this study suggest that parents’working model of the child is an important factor to understand parent-child attachment relationships and their interactions. The understanding of parents’ working model of the child is thought to enrich our understanding of disordered parent-child relationships and to provide useful informations for specific and successful treatments.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Proceedings of the Optical Society of Korea Conference
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• 1989.02a
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• pp.95-98
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• 1989

A new associative memory model using the SDF filter, one of the multiple filter for pattern recognition, is suggested in this paper. The SDF filter characteristics such as pattern classification lets the memorized patterns have orthogonal characteristics one another, so that enhances the associative memory's retrieval ability to the original pattern. The computer simulation shows that this new model is very useful in case that the imput patterns are seriously distorted and the cross-correlation between the memorized patterns is very high.