• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.6
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• pp.655-662
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• 2012

Gas leakage in an oil refinery causes damage to the environment and unsafe conditions. Therefore, it is necessary to develop a technique that is able to detect the location of the leakage and to filter abnormal gas-leakage signals from normal background noise. In this study, the adaptation filter of the finite impulse response (FIR) least mean squares (LMS) algorithm and a cross-correlation function were used to develop a leakage-predicting program based on LABVIEW. Nitrogen gas at a high pressure of 120 kg/$cm^2$ and the assembled equipment were used to perform experiments in a reverberant chamber. Analysis of the data from the experiments performed with various hole sizes, pressures, distances, and frequencies indicated that the background noise occurred primarily at less than 1 kHz and that the leakage signal appeared in a high-frequency region of around 16 kHz. Measurement of the noise sources in an actual oil refinery revealed that the noise frequencies of pumps and compressors, which are two typical background noise sources in a petrochemical plant, were 2 kHz and 4.5 kHz, respectively. The fact that these two signals were separated clearly made it possible to distinguish leakage signals from background noises and, in addition, to detect the location of the leakage.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.116-123
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• 2013

This paper represents generation of time-varying underwater acoustic channels by performing scattering simulation with time-varying ocean surface and Kirchhoff approximation. In order to estimate the time-varying ocean surface, 1D Pierson-Moskowitz ocean power spectrum and Gaussian correlation function were used. The computed scattering coefficients are applied to the amplitudes of each impulse of BELLHOP simulation result. The scattering coefficients are then compared with measured doppler spectral density of signal components which were scattered from ocean surface and the correlation time used in the Gaussian correlation function was estimated by the comparison. Finally, bit-error-rate and channel correlation simulations were performed with the generated time-varying channel based on passive time-reversal communication scenario.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.462-470
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• 2002

Wideband speech, characterized by a bandwidth of 50∼7000 ㎐, sounds more natural and intelligible, and is less tiring to listen to when compared to narrowband speech characterized by a bandwidth of 300∼3400 ㎐. Wideband speech coders, however, have not been as successful as the narrowband speech coders because of their higher bit rate. In this paper, we propose a new wideband speech coder which combines the European standard of a narrowband speech coder, i.e., GSM-EFR, and a transform coder using the discrete wavelet transform. The proposed wideband speech coder operates as follows input speech is first split into two subbands with equal bandwidth and the two subband signals are coded and decoded by each subband coder. A GSM-EFR is adopted as a lower subband coder and a subband coder with wavelet transformed speech is designed for a upper subband coder. The total bit rate of the proposed coder is 18.9kbps (12.2 kbps for lower band coder and 6.7 kbps for upper band coder), and informal listening test results have shown that the proposed coder has comparable speech quality to that of G.722 with 56 kbps.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.441-446
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• 2009

This paper proposes an automatic indexing algorithm of golf video using audio information. In the proposed algorithm, the input audio stream is demultiplexed into the stream of video and audio. By means of Adaboost-cascade classifier, the continuous audio stream is classified into announcer's speech segment recorded in studio, music segment accompanied with players' names on TV screen, reaction segment of audience according to the play, reporter's speech segment with field background, filed noise segment like wind or waves. And golf swing sound including drive shot, iron shot, and putting shot is detected by the method of impulse onset detection and modulation spectrum verification. The detected swing and applause are used effectively to index action or highlight unit. Compared with video based semantic analysis, main advantage of the proposed system is its small computation requirement so that it facilitates to apply the technology to embedded consumer electronic devices for fast browsing.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.447-453
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• 2020

In this paper, we propose a system to extract effective speaker representations from a speech signal using a deep learning method. Based on the fact that speech signal contains identity unrelated information such as text content, emotion, background noise, and so on, we perform a training such that the extracted features only represent speaker-related information but do not represent speaker-unrelated information. Specifically, we propose an auto-encoder based disentanglement method that outputs both speaker-related and speaker-unrelated embeddings using effective loss functions. To further improve the reconstruction performance in the decoding process, we also introduce a discriminator popularly used in Generative Adversarial Network (GAN) structure. Since improving the decoding capability is helpful for preserving speaker information and disentanglement, it results in the improvement of speaker verification performance. Experimental results demonstrate the effectiveness of our proposed method by improving Equal Error Rate (EER) on benchmark dataset, Voxceleb1.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.466-475
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• 2024

Matched-Field Processing (MFP) is a model-based approach that requires accurate knowledge of the ocean environment and array geometry (e.g., array tilt) to localize underwater acoustic sources. Consequently, it is inherently sensitive to model mismatches. In contrast, the waveguide invariant-based approach (also known as array invariant) offers a simple and robust means for source-range estimation in shallow waters. This approach solely exploits the beam angles and travel times of multiple arrivals separated in the beam-time domain, requiring no modeling of the acoustic fields, unlike MFP. This paper extends the waveguide invariant-based approach to shallow water environments featuring a shallow pit, where the waveguide invariant is not defined due to the complex bathymetry. An in-depth performance analysis is conducted using experimental data and numerical simulations.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.146-146
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• 2020

최근 하천의 유사 중 소류사량을 계측하기 위해 사용된 기존의 물리적 소류사 샘플러를 이용한 직접계측방법은 홍수 시에 깊은 수위와 빠른 유속, 계측 절차상의 위험성 때문에 현장관측이 매우 어려운 한계를 극복하기 위해 현업에서는 소류사량을 간접적으로 추정하는 이론식에 의한 방법이 광범위하게 활용되고 있으나 이 방법 또한 추정이론식의 적용지역, 적용방법에 따라 결과가 수십배 이상 큰 차이를 나타나 실제 활용성에 대한 문제점이 있다. 이러한 기존의 소류사량 측정 방법의 문제점을 보완하기 위해 소류사량을 간접계측하는 방법이 활발히 제안되고 있다. 대표적인 방법으로 하상 이동 시 소류사의 충돌음을 음향센서로 계측하여 신호처리를 통해 소류사량을 추정하는 계측기기인 하이드로폰이 있다. 그러나 국외의 소류사량 간접계측 장치는 소류사량의 운송량이 많을 경우 음향신호 중접으로 인해 펄스 수의 감소, 감지 가능한 입경크기의 제한 등의 문제가 있다. 또한 국내의 백무평(2018)이 제안한 소류사 분석 방법인 대역통과방법(B-P Method)는 소류사량 추정에 있어서 기존의 방법과는 달리 주파수 특성을 반영하여 이전 연구들에 비하여 펄스 검출률을 향상시겼지만 이 방법은 극히 낮은 저유속과 작은 입경이라는 실험조건에서 이루어졌다는 제한사항이 있다. 따라서 본 연구는 다양한 입경과 고유속에 대하여 소류사량을 정량화할 수 있는 방법을 제시하기 위해 소류사 입경이 하이드로폰에 충돌할 때 발생하는 단독입자의 충돌음을 계측하기 위한 실외 수로실험장치를 구축하여 계측을 수행하였다. 실험은 현장에서 대표 시료로 분류된 몇 가지 입경에 대해서 유량 변화에 따른 충돌음향과 소류사량 그리고 소류사 입경크기에 따른 하이드로폰에서 인지되는 음향 특성을 계측 및 분석하였다. 연구결과 입경 크기 및 수리조건 변화에 따른 하이드로폰의 충돌음향 특성을 파악하여 단일 입경별 소류사량 추정관계식을 산출하였다. 또한 산출된 추정 관계식의 특성치와 공급 소류사량 간의 관계를 유도해 보았다. 향후 혼합입경에 대한 실험과 추정 관계식 신뢰성 검토 후 추가적으로 다양한 실험조건을 고려하여 실제 하천에 운송되는 소류사량과의 교정관계 확립을 진행한다면 국내 소류사량 데이터 수집을 위한 현장 설치까지 가능할 것으로 사료된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• Composites Research
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• v.13 no.4
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• pp.54-66
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• 2000

Interfacial and microfailure properties of carbon fiber/epoxy matrix composites were evaluated using both tensile fragmentation and compressive Broutman tests with an aid of acoustic emission (AE) monitoring. A polymeric maleic anhydride coupling agent and a monomeric amino-silane coupling agent were used via the electrodeposition (ED) and the dipping applications, respectively. Both coupling agents exhibited significant improvements in interfacial shear strength (IFSS) compared to the untreated case under tensile and compressive tests. The typical microfailure modes including fiber break of cone-shape, matrix cracking, and partial interlayer failure were observed during tensile test, whereas the diagonal slippage in fiber ends was observed under compressive test. For both loading types, fiber breaks occurred around just before and after yielding point. In both the untreated and treated cases AE amplitudes were separately distributed for the tensile testing, whereas they were closely distributed for the compressive tests. It is because of the difference in failure energies of carbon fiber between tensile and compressive loading. The maximum AE voltage for the waveform of carbon or basalt fiber breakages under tensile tests exhibited much larger than those under compressive tests, which can provide the difference in the failure energy of the individual failure processes.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.61-64
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• 1999

기존의 CELP 보코더에서, 무성음에 대한 별도의 처리 없이 유성음과 동일하게 처리하였다. 유성음과 무성음은 발성모델측면에서 임펄스열과 랜덤 잡음으로 각각 다름에 도 불구하고 동일하게 처리함으로써 합성음에서 음질의 저하 및 계산량과 전송률 측면에서 손실을 가져왔다. 또, U/V(Unvoiced /voiced) 분류기를 사용하는 경우에는 U/V 분류기의 성능에 따라 합성음의 음질저하의 정도의 차이가 심하다. 본 논문에서는 에러율과 전처리 계산량을 쳐소로 할 수 있는 U/V 분류기를 사용하여 CELP 보코더에서 전송률을 감소시키는 방법을 제안한다. CELP 보코더에서는 스펙트럼 정보를 LPC 파라미터로 추출한 후 다시 전송형 파라미터인 LSP(Line Spectrum Frequency)로 변환한다 새로운 린/V 분류기는 이 LSP 파라미터를 이용한다. LSP 파라미터의 주파수영역 분포도와 간격정보를 이용하여 U/V를 결정하게 된다 제안한 방법을 5.3kbps ACELP에 적용하여 성능 평가를 실시하였다 실험결과 음질의 저하 없이 $5.6\%$ (280bps)의 전송률을 감소할 수 있었다.