• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.327-332
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• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than loom.

• Korean Journal of Optics and Photonics
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• v.12 no.4
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• pp.263-269
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• 2001

The influences of background and environmental noise on coincidence detection are investigated with entangled photons produced by parametric down-conversion process. When the down-converted photons are mixed with thermal light, the coincidence rate did not vary with increasing noise level because the accidental coincidences are discriminated at the short resolving time window. The entangled photon source and the coincidence technique can effectively be used for a noise-free communication channel in the new field of quantum information transmission and processing. ssing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.728-732
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• 2010

GIS(Gas insulated switching gear) is power equipment with excellent dielectric strength and is economy merit in high confidence and stability. Recently, because equipment of GIS was occurring problem of confidence used for a long time, partial discharge on-line diagnosis systems have been importantly recognized. Partial discharge (PD) detection is an effective means for monitoring and evaluation of dielectric condition of gas insulated system (GIS). The ultra-high-frequency (UHF) PD detection technique can detect and locate the PD sources inside GIS by detecting electromagnetic wave emitted from PD source. Therefore, real-time diagnostic system using UHF detection method has been developed for this application is being expanded gradually. However, the signal of partial discharge occurring in SF6 gas is very weak and susceptible to external noises which mainly consist of PD in air. Thus, it is important to distinguish the PD in SF6 gas more sensitively from the external noises. Unfortunately, these external noise signals and the partial discharge signals have very similar characteristics. Therefore, to solve this problem, we need the signal processing method for distinguish partial discharge signals with external noise signals for improvement of SNR(signal to noise ratio) and sensitivity. In this paper, we proposed internal signal processing method for removing external noise signals with built-in pre.amplifier and frequency conversion circuit.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.144-151
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• 2006

Sound generated from a moving vehicle often carries information on the condition of vehicle, for example, whether it has faults or not, where the fault exists. The latter is possible especially by MFAH(moving frame acoustic holography) and beamforming method. MFAH is applicable to the sound source of pure tone or narrow band noise. For the beamforming method, we have to know what kind of wave the sound source radiates, for example, plane wave or spherical wave. That is, whether the above methods are applicable depends on the characteristics of sound source. To apply these methods to the fault detection, we have to know the characteristics of wave from faults. In this research, a machine diagnosis technique based on the above holographic approaches is introduced to find the position of faults. The signal due to faults is modeled based on the fact that the faults radiate impulsive noise, and analyzed in time and frequency domain. The way how MFAH and beamforming method can be used is introduced to find the position of source.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.637-640
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• 2005

We propose a sound source localization method using the Head-Related-Transfer-Function (HRTF) to be implemented in a given platform. HRTFs contain not only the information regarding proper time delays but also phase and magnitude distortions due to diffraction and scattering by the shading object. Therefore, a set of HRTFs for any given platform provides a substantial amount of information as to the whereabouts of the source. In this study, we introduce new phase criterion in order to find the sound source location in accordance with the HRTF database empirically obtained in an anechoic chamber with the given platform. Using this criterion, we analyze the estimation performance of the proposed method in a household environment.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.933-946
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• 2021

In the non-orthogonal multiple access (NOMA) system, multiple user signals on the single carrier are superimposed in a non-orthogonal manner, which results in the interference between non-orthogonal users and noise interference in the channel. To solve this problem, an improved algorithm combining regularized zero-forcing (RZF) precoding with minimum mean square error-serial interference cancellation (MMSE-SIC) detection is proposed. The algorithm uses RZF precoding combined with successive over-relaxation (SOR) method at the base station to preprocess the source signal, which can balance the effects of non-orthogonal inter-user interference and noise interference, and generate a precoded signal suitable for transmission in the channel. At the receiver, the MMSE-SIC detection algorithm is used to further eliminate the interference in the signal for the received superimposed signal, and reduce the calculation complexity through the QR decomposition of the matrix. The simulation results show that the proposed joint detection algorithm has good applicability to eliminate the interference of non-orthogonal users, and it has low complexity and fast convergence speed. Compared with other traditional method, the improved method has lower error rate under different signal-to-interference and noise ratio (SINR).

• Journal of Sensor Science and Technology
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• v.14 no.3
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• pp.191-197
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• 2005

When fabricating a vision chip, we should consider the noise problem, such as the fixed pattern noise(FPN) due to the process variation. In this paper, we propose an edge-detection circuit based on biological retina using the offset-free column readout circuit to reduce the FPN occurring in the photo-detector. The offset-free column readout circuit consists of one source follower, one capacitor and five transmission gates. As a result, it is simpler and smaller than a general correlated double sampling(CDS) circuit. A vision chip for edge detection has been designed and fabricated using $0.35\;{\mu}m$ 2-poly 4-metal CMOS technology, and its output characteristics have been investigated.

• Proceedings of the Optical Society of Korea Conference
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• 1990.02a
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• pp.242-247
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• 1990

By self-homodyne method we measured the relative phase fluctuation of a light wave. Balanced detection system can eliminate local oscillator excess noise and multiport detection makes it possible ot measure the phase change of the signal beam. Deriving the SB(Signal Beam) and the LO(Local Oscillator) from the same laser source, we find the SB maintain constant phase relative to that of the LO. We have introduced a phase fluctuation in the SB by modulating the beam path of the SB. The measured phase fluctuation agreed well with the predicted one, thereby we confirmed the reliability of our system.

• Journal of Sensor Science and Technology
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• v.8 no.2
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• pp.148-153
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• 1999

In this paper, we developed and implemented the geological magnetic filter for the improvements of the signal to noise ratio of the magnetic detection system. Using the geological magnetic filter, we can remove the coherent noises in the time domain and improve the signal to noise ratio of the magnetic detection system. Numerical simulation results show that geological magnetic filter can excellently remove the sensor misalignment effects and the regular short range local noise as well as it delete the coherent noises. We confirmed that the geological magnetic filter improved the signal to noise ratio about 19dB and deleted the coherent noises with restoring the source magnetic signal through experiments by implemented system.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.