• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.268-275
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• 2008

In this paper, we introduce a new method for detecting and estimating faults on a power line using the time-frequency domain reflectometry system. The system rests upon time-frequency signal analysis and uses a chirp signal which is multiplied by Gaussian envelope. The chirp signal is used as a reference signal, and we can get the reflected signal from a fault on a wire. To detect and estimate faults, we analyze the reflected signal by Wigner time-frequency distribution function and normalized time-frequency cross correlation function. In this paper we design an optimal reference signal for power line and implement a system for estimating fault distance on a power line with the TFDR implemented by PXI equipments. This approach is verified by some experiments with HIV 2.25mm power lines.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.91-94
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• 2003

In this paper, we achieve implementation of a Time-Frequency Domain Reflectometry(TFDR) system through comparatively low performance(100MS/s) PCI extensions for Instrumentation(PXI). The TFDR is the general methodology of Time Domain Reflectometry(TDR) and Frequency Domain Reflectometry(FDR). This methodology is robust in Gaussian noises, because the fixed frequency bandwidth is used. Moreover, the methodology can get more information of the fault by using the normalized time-frequency cross correlation function. The Arbitrary Waveform Generator(AWG) module generates the input signal, and the digital oscilloscope module acquires the input and reflected signals, while PXI controller module performs the control of the total PXI modules and execution of the main algorithm. The maximum range of measurement and the blind spot are calculated according ta variations of time duration and frequency bandwidth. On the basis of above calculations, the algorithm and the design of input signals used in the TFDR system are verified by real experiments. The correlation function is added to the TDR methodology for reduction of the blind spot in the TFDR system.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1803-1804
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• 2006

The purpose of this paper is to implement a Labview based TFDR Real Time system through the instruments of Pci eXtensions for Instrumentation(PXI). The proposed load impedance measurement algorithm was verified by experiments via the implemented real time system. The TFDR real time system consisted of the reference signal design, signal generation, signal acquisition, algorithm execution and results display parts. To implement real time system, all of the parts wore programmed by the Labview which is one of graphical programming languages. In the application software implemented by the Labview we were able to design a suitable reference signal according to the length and frequency attenuation characteristics of the target cable and controled the arbitrary waveform generator(ZT500PXI) of the signal generation part and the digital storage oscilloscope(ZT430PXI) of the signal acquisition part. By using the TFDR real time system with the terminal resistor on the target cable, we applied to the load impedance measurements. In the proposed load impedance algorithm a normalized time-frequency cross correlation function and a cross time-frequency distribution function was employed to calculate the reflection coefficient and phase difference between the input and the reflected signals.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.521-530
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• 2005

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry(TFDR), isproposed to detect and estimate a fault in a transmission line. Traditional reflectometry methodologies have been achieved either in the time domain or in the frequency domain only. However, the TFDR can jump over the performance limits of the traditional reflectometry methodologies because the acquired signal is analyzed in time and frequency domain simultaneously. In the TFDR, the new reference signal and the novel TFDR algorithm are proposed for analyzing the acquired signal in the time-frequency domain. Because the reference signal of Gaussian envelop chirp signal is localized in the time and frequency domain simultaneously, it is suitable to the analysis in the time-frequency domain. In the proposed TFDR algorithm, the time-frequency distribution function and the normalized time-frequency cross correlation function are used to detect and estimate a fault in a transmission line. That algorithm is verified for real-world coaxial cables which are typical transmission line with different types of faults by the TFDR system composed of real instruments. The performance of the TFDR methodology is compared with that o( the commercial time domain reflectomeoy(TDR) experiments, so that concludes the TFDR methodology can detect and estimate the fault with smaller error than TDR methodology.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.9
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• pp.1029-1039
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• 1992

This paper presents the filtering method which is processed on the frequency domain among Hangul character recognition methods. It is processed the Hangul character parrern with spatial positioning modulation and mapped the Hangul character element which have spatial position variant feature onto frequency domain, at this time, normalized spatial position and so normalized the character size in frequency domain. And it is grouped the Hangul character element according to the generating position and set the standard pattern, and used each standard character element pattern with character element filter and filtering the character pattern of Hangul character, it is derived the normalized cross correlation function and the coherence function led to the filtering results, and calculated classification threshold.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.2
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• pp.122-129
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• 2014

Identification of the whipping response out of the combined wave-vibration response of a flexible sea going vessel is one of the most interesting research topic from ship designer's point of view. In order to achieve this goal, a novel methodology based on the wavelet cross-correlation technique was proposed in this paper. The cross-correlation of the wavelet power spectrum averaged across the frequency axis was introduced to check the similarity between the combined wave-vibration response and impulse response. The calculated cross-correlation of the wavelet power spectrum was normalized by the auto-correlation of the each spectrum with zero time lag, eventually providing the cross-correlation coefficient that stays between 0 and 1, precisely indicating the existence of the impulse response buried in the combined wave-vibration response. Additionally, the weight function was introduced while calculating the cross-correlation of the two spectrums in order to filter out the signal of lower frequency so that the accuracy of the similarity check becomes as high as possible. The validity of the proposed methodology was checked through the application to the artificially generated ideal combined wave-vibration signal, together with the more realistic signal obtained by running 3D hydroelasticity program WISH-Flex. The correspondence of the identified whipping instances between the results, one from the proposed method and the other from the calculated slamming modal force, was excellent.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.551-554
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• 2005

The method of the reduction of the automotive induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. Thus Normalized FXLMS algorithm was developed to improve the control performance under the rapid acceleration. The advantage of Normalized FXLMS algorithm is that the step size is no longer constant. Instead, it varies with time. But there is one additional practical difficulty that can arise when a nonstationary input is used. If the input is zero for consecutive samples, then the step size becomes unbounded. So, in order to solve this problem. the Correlation FXLMS algorithm was developed. The Correlation FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Correlation FXLMS Is presented in comparison with that of the other FXLMS algorithms based on computer simulations.