• 한국해양공학회지
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• 제34권3호
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 C
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• pp.1691-1693
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• 2002

Acoustic partial discharge detection has been used on GIS testing for more than 10 years. Sensitivities show that most of critical defect types can be detected with a reasonable signal-to-noise ratio. The paper reports on acoustic partial discharge detection comparable to sensitive electrical PD(partial discharge) measuring method.

• Journal of Biosystems Engineering
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• 제22권1호
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• pp.41-48
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• 1997

A nondestructive quality inspection technique using acoustic impulse response method was studied to investigate the feasibility of egg shell inspection. An experimental system was built to generate impact force, to measure the response signal and to analyze the frequency spectrum. This system includes an impulse generating unit, an egg holding seat, a microphone with preamplifier, and a digital oscilloscope connected to Personal Computer by RS-232C interface. The factors such as impulse generating method, egg holding method, and sensor location were evaluated by analyzing the power spectrum density of the measured signal. The results obtained are summarized as follows : 1. From the sampled eggs, the proper conditions for detecting damaged eggs were found as followings; ceramic for the impact ball material, rubber for egg seat material, 20 degrees for an impact angle of pendulum, 10mm for the distance between egg and sensor, the sharp side for impacting part, and 180 degrees for the location of sensor. 2. Examination of the Fourier transformed analysis in beth normal and damaged eggs revealed that those factors such as the resonant frequency, a number of peak frequencies and the magnitude of power spectrum were important to detect damaged eggs.

• 비파괴검사학회지
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• 제29권5호
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• pp.485-492
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• 2009

열피로균열은 원자력발전소의 운영 과정에서 구조물의 수명을 결정짓는 문제로 정량적인 탐지가 어렵다. 현재 산업현장에서 구조물에 대한 건전성을 정량적으로 평가하기 위해서 radiographic탐상 및 초음파탐상, eddy current 등 다양한 종류의 비파괴검사 기술이 사용되고 있지만, 위에 열거한 비파괴탐상법의 경우 균열이 일정부분 진행된 이후에나 검출이 가능하다는 제한 사항이 있다. 이러한 이유로 구조물에 대한 연속적인 모니터링이 가능한 장점을 가진 음향방출탐상법(acoustic emission testing)이 대안적인 검사방법으로 제시되고 있다. 일반적으로 구조물이나 장비의 건전성에 영향을 미치는 모든 요인들이 음향방출 신호의 발생을 일으키기 때문에, 음향방출을 이용한 결함 탐상시 함께 발생하는 노이즈를 구분하는 일은 음향방출을 연구하는 대부분의 연구원의 주요 업무중 하나라고 할 수 있다. 이에 본 연구에서는 열피로 사이클 조건에서의 배관에 대한 음향방출 신호를 수집하여 유효한 균열 신호를 노이즈로부터 구분하고자 하는 목적으로 진행되었다. 그 방법으로 유사한 조건에서 실시한 결과를 이용하여 노이즈 필터링 조건을 설정하였으며, 균열의 신호를 찾아내기 위한 방법으로 음향파형(waveform) 구분법을 제시하였다. 이 실험에서 도출된 결과는 구조물의 결함을 탐지하는 실시간 연속적 모니터링 기술 개발에 대한 기초자료로 사용될 수 있을 것으로 기대된다.

• 대한음성언어의학회:학술대회논문집
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• 대한음성언어의학회 2003년도 제19회 학술대회
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• pp.208-211
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• 2003

This paper introduces a history and achievements of the research activities on screening of laryngeal diseases using acoustic analysis. First domestic and international research trends are introduced. Next brief introduction of the research results by the authors are mentioned. First, classification method of the laryngeal diseases using neural network is summarized. Then similar research using ARS (Automatic Response System) is mentioned. Finally, current research activities on screening of laryngeal diseases on internet is introduced.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 C
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• pp.1918-1920
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• 2000

In this paper, acoustic signals in GIS were analyzed by using wavelet transform and FFT to distinguish sound source caused by collision of particles and partial discharges. As a result, the analysis using wavelet transform was more accurate than that using FFT. Therefore, wavelet transform was useful technique to analyze the acoustic signals in GIS.

• 한국생산제조학회지
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• 제19권1호
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• pp.7-14
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• 2010

AE(acoustic emission) sensor has been used for a state monitoring and observation during a ultra-precision machining because AE signal, which has high frequency range, is sensitive enough. In case of ceramic fabrication, a monitoring of machining state is important because of its hard and brittle nature. A machining characteristic of ceramic is susceptibly different in accordance with variable machining conditions. In this study, Yttria($Y_2O_3$) ceramic was fabricated using the ultra-precision lapping process with in-process electrolytic dressing(IED) method. And the surface machining characteristic and AE sensor signal were compared and analyzed.

• 비파괴검사학회지
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• 제27권3호
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• pp.262-267
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• 2007

Detection of gas leak from a tube is a very important issue in the quality control of machines such as the heat exchanger of an air-conditioner, because leakage of operating gas directly reduces the performance of machines. The acoustic emission (AE) method is a common way to detect leak of gas, however its application under the environment of mechanical vibration is restricted since most AE detectors are very sensitive to external vibration noise. In order to overcome this problem, we propose a method based on the mode analysis of the Lamb wave. In this method, the dominant Lamb mode and its frequency are found first, and then a proper band-pass filter is used to retain only this frequency component. In this way, we could improve the SNR (signal-to-noise ratio) of AE signal generated by gas leak from the tube even under vibratory environment.

• 대한기계학회논문집
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• 제17권8호
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• pp.1910-1920
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• 1993

An experimental study to investigate the unconventional chip formation called triangulation of chip in cutting with a SPRT (self-propelled rotary tool) is performed using acoustic emission (AE) signal analysis. In doing that, a quantitative model of the AE RMS signal in triangulation with a SPRT is first developed. The predicted results from this model show good correlation between the AE RMS signal and the general characteristics of triangular chip formation. Then, effects of various process parameters such as cutting conditions (cutting speed, depth of cut, oblique angle and normal rake angle) and the work material properties on the chip formation in cutting with a SPRT are explored. Special attention is paid to the work material properties which are found to have significant effects on triangulation.

• 한국전기전자재료학회논문지
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• 제14권1호
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• pp.84-92
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• 2001

In this papers, we proposed the new method in order to diagnosis aging state of transformers. For wavelet transform, Daubechies 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 each acoustic emission signal. Also, these coefficients are used to identify normal and fault signal of internal partial discharge in transformer. As improved method for classification use neural network. Extracted statistical parameters are input into an back-propagation neural network. The number of neurons of hidden layer are obtained through Result of Cross-Validation. The network, after training, can decide whether the test signal is early aging state, alst aging state or normal state. In quantity analysis, capability of proposed method is superior to compared that of classical method.