• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.21-27
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• 2019

In this paper, we propose a deep auto-encoder-based pipe leak detection (PLD) technique from time-series acoustic data collected by microphone sensor nodes. The key idea of the proposed technique is to learn representative features of the leak-free state using leak-free time-series acoustic data and the deep auto-encoder. The proposed technique can be used to create a PLD model that detects leaks in the pipeline in an unsupervised learning manner. This means that we only use leak-free data without labeling while training the deep auto-encoder. In addition, when compared to the previous supervised learning-based PLD method that uses image features, this technique does not require complex preprocessing of time-series acoustic data owing to the unsupervised feature extraction scheme. The experimental results show that the proposed PLD method using the deep auto-encoder can provide reliable PLD accuracy even considering unsupervised learning-based feature extraction.

• The Journal of the Acoustical Society of Korea
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• 제24권2E호
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• pp.46-53
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• 2005

Agency for Defense Development (ADD) developed the Submarine Acoustic Information Management System (SAIMS Version 1.0) capable of interfacing some submarine sensors in operation and predicting detection environments for sonars. The major design concepts are as follows: 1) A proper acoustic model is examined and optimized to cover wide spectra of frequency ranges for both active and passive sonars. 2) Interfacing the submarine sensors to an electric navigation chart, the system attempts to maximize the applicability of the information produced. 3) The state-of-the-art database in large area is built and managed on the system. 4) An algorithm, which is able to estimate a full sound speed profile from the limited oceanographic data, is developed and employed on the system. This paper briefly describes design concepts and algorithms embedded in the SAIMS. The applicability of the SAIMS was verified through three sea experiments in October 2003-February 2004.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 춘계학술대회 논문집 유기절연재료 전자세라믹 방전플라즈마 일렉트렛트 및 응용기술
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• pp.170-176
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• 2002

In this papers, we proposed the feature extraction method due to partial discharge type of transformers. For wavelet transform, Daubechie's filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion, skewness, kurtosis) about acoustic emission signal generated from each partial discharge type. The defects which could occur in a transformer were simulated by using needle-plane electrode, IEC electrode and Void electrode. Also, these coefficients are used to identify signal of partial discharge type electrode fault in transformer. As a result, from compare of acoustic emission amplitude and acoustic average value, we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. otherwise, In case of skewness and kurtosis, we are obtained results of Needle-Plane electrode electrode> Void electrode> IEC electrode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권9호
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• pp.1632-1652
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• 2011

This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes' particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes' particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

• Applied Microscopy
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• 제50권
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• pp.25.1-25.11
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• 2020

Scanning acoustic microscopy (SAM) or Acoustic Micro Imaging (AMI) is a powerful, non-destructive technique that can detect hidden defects in elastic and biological samples as well as non-transparent hard materials. By monitoring the internal features of a sample in three-dimensional integration, this technique can efficiently find physical defects such as cracks, voids, and delamination with high sensitivity. In recent years, advanced techniques such as ultrasound impedance microscopy, ultrasound speed microscopy, and scanning acoustic gigahertz microscopy have been developed for applications in industries and in the medical field to provide additional information on the internal stress, viscoelastic, and anisotropic, or nonlinear properties. X-ray, magnetic resonance, and infrared techniques are the other competitive and widely used methods. However, they have their own advantages and limitations owing to their inherent properties such as different light sources and sensors. This paper provides an overview of the principle of SAM and presents a few results to demonstrate the applications of modern acoustic imaging technology. A variety of inspection modes, such as vertical, horizontal, and diagonal cross-sections have been presented by employing the focus pathway and image reconstruction algorithm. Images have been reconstructed from the reflected echoes resulting from the change in the acoustic impedance at the interface of the material layers or defects. The results described in this paper indicate that the novel acoustic technology can expand the scope of SAM as a versatile diagnostic tool requiring less time and having a high efficiency.

• Journal of information and communication convergence engineering
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• 제14권2호
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• pp.78-83
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• 2016

In underwater acoustic communication, the transmitted signals are severely influenced by the reflections from both the sea surface and the sea bottom. As very large reflection signals from these boundaries cause an inter-symbol interference (ISI) effect, the communication quality worsens. A channel estimation-based equalizer is usually adopted to compensate for the reflected signals under the acoustic communication channel. In this study, a feed-forward equalizer (FFE) with the least mean squares (LMS) algorithm was applied to a quadrature phase-shift keying (QPSK) transmission system. Two different types of equalizers were adopted in the QPSK system, namely a real-coefficient equalizer and a complex-coefficient equalizer. The performance of the complex-coefficient equalizer was better than that of two real-coefficient equalizers. Therefore, a Hilbert transform was applied to the real-coefficient binary phase-shift keying (BPSK) system to obtain a complex-coefficient BPSK system. Consequently, we obtained better results than those of a real-coefficient equalizer.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.357-358
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• 2006

We propose the robust PBFLMS in noises, which is the enhanced acoustic echo canceller using ACPBF-LMS(Alternative Constrained Partitioned Block Frequency domain Least Mean Square) algorithm. The defect of the block structure filtering is the deterioration of convergence efficiency from noise and interference. To improve the performance of convergence efficiency, noise effect should be reduced. The new method of reducing noise effect is proposed, which apply the estimated background noise to adaptive filter step size. By experiments, the proposed acoustic echo canceller has TCL of 50dB, and always provides faster convergence speed and lower complexity than the full-tap NLMS. We also carried out an implementation of PBFLMS using ARM9EJ-S.

• 융합신호처리학회논문지
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• 제11권3호
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• pp.203-208
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• 2010

본 논문에서는 소나 시스템을 통해 획득된 수중 음향 신호를 디지털 영상의 형태로 변환한다. 그리고 이러한 형태의 영상에 대해 영상 처리 기법을 도입하여 표적 후보를 탐지하고, 이들 영역에 대해 정보를 강화하는 알고리즘을 제안한다. 수중 표적의 탐지 과정은 우선 수중음향신호 영상에서 불규칙한 형태로 분포하고 있는 배경 잡음을 추정하여 재구성한 뒤, 원 영상에서 배경 영상을 제거하여 초기 표적 후보군을 획득한다. 또한 도플러 신호 정보를 가공하여 가중치 맵을 생성하고, 배경잡음이 제거된 영상에 대해 가중치 맵을 이용한 필터링 과정을 수행함으로써 표적 후보에 대한 정보를 보다 정확히 확보하고, 단일프레임에서의 표적 후보 정보를 강화한다. 본 논문에서는 시뮬레이션으로 획득된 수중음향신호에 대해 제안된 알고리즘을 적용하여, 불규칙적으로 발생하게 되는 잡음이 대부분 제거됨을 확인하였고, 필터링 및 표적 탐지 과정을 통해 수중음향신호 영상에서 표적이 더욱 명확히 표시됨을 확인하였다.

• 한국음향학회지
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• 제38권5호
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• pp.607-613
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• 2019

본 논문은 external knowledge를 사용한 lattice 없는 상호 정보 최대화(Lattice Free Maximum Mutual Information, LF-MMI) 기반 음향 모델링 방법을 제안한다. External knowledge란 음향 모델에서 사용하는 학습 데이터 이외의 문자열 데이터를 말한다. LF-MMI란 심층 신경망(Deep Neural Network, DNN) 학습의 최적화를 위한 목적 함수의 일종으로, 구별 학습에서 높은 성능을 보인다. LF-MMI에는 DNN의 사후 확률을 계산하기 위해 음소의 열을 사전 확률로 갖는다. 본 논문에서는 LF-MMI의 목적식의 사전 확률을 담당하는 음소 모델링에 external knowlege를 사용함으로써 과적합의 가능성을 낮추고, 음향 모델의 성능을 높이는 방법을 제안한다. External memory를 사용하여 사전 확률을 생성한 LF-MMI 모델을 사용했을 때 기존 LF-MMI와 비교하여 14 %의 상대적 성능 개선을 보였다.

• 한국음향학회지
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• 제38권1호
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• pp.114-119
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• 2019

천해에서 전송되어진 음향 신호는 해수면 및 바닥과 같은 경계로부터의 다중 반사파에 의해 많은 영향을 받는다. 경계로부터의 매우 큰 반사 신호는 심볼 간 간섭을 일으켜 수중 음향 통신의 성능을 저하시키는 요인이 된다. 일반적으로 이러한 종류의 음향 채널에서 반사된 신호를 방지하기 위해 파형 정형 필터를 사용되고 있다. 특히 상승 코사인 필터가 널리 사용되며, 이 필터는 전송 신호의 대역폭을 제한하는 데에도 사용된다. 본 연구에서는 천해에서 영상 데이터 전송을 위한 상승 코사인 필터를 평가하며, 이를 바탕으로 새로운 수정된 상승 코사인 필터를 제안하고 평가 하였다. 수중 음향 통신 시뮬레이션에 사용된 통신 시스템은 직교 위상천이변조(Quadrature Phase Shift Keying, QPSK) 시스템이고, 송수신 거리와 심볼율을 달리하여 수행한 결과, 최저 1.0 %에서 최고 32 %의 에러 감소율을 보였다.