• 한국해양공학회지
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• 제9권2호
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• pp.167-174
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• 1995

The anomlous signal, anomaly, recorded by a sub-bottem profiler is analized for exploration of buried objects in the ocean, This anomaly is known as a signal diffracted from the edge of the buried object. Signals obtained from model that and numerical simulation are analized for investigating characteristics of the diffracted signal. From this study a diffracted signal and a non-diffracted signal can be identified, and the location of the object can be obtained. In order to identify an object in the seafloor the dimension of the object should be greater than the wave length used for exploration, and the acoustic impedance should be much greater than that of sediments. A 2-trace stacking of the signals can enhance the feature of strongly diffracted signals whereas it can diminish weak signals.

• 동력기계공학회지
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• 제14권6호
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• pp.41-46
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• 2010

Acoustic emission (AE) technique is a well-known non-destructive test technique. Fatigue crack growth test was performed using SM53C to check up the AE signal occurred by crack growth, so AE system was used to detect the crack signal. Features calculated by the AE signals were analyzed to evaluate the steps divided the crack growth into three. The steps, initiation, growth and breaking, were separated by velocity of the crack growth. Time waveform and power spectrum were created by the AE signal of each one of the steps and compared. In the feature domains, it was found that AE values changed rapidly as the velocity of the crack increasing.

• 한국음향학회지
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• 제14권4호
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• pp.12-20
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• 1995

본 논문은 충격 음향법에 의한 원통형 물체의 결함 검출 방법에 관한 원리와 실험 결과를 기술한다. 원통형 물체가 가지게 되는 공진 주파수는 물체의 직경, 길이 등의 물리적 크기에 따라 결정되며 이러한 원통형 물체를 자유 공진 시킬 경우 구조물 고유에 주파수 및 고조파 성분이 내포된 음향을 방생시킨다. 결함이 존재하는 물체에 충격ㄷ이 가해질 경우 발생하는 음향은 정상의 경우와 구별되며, 주파수 성분 분석을 통해 보다 명확한 식별이 가능하다. 본 연구에서 적용된 음향 충격법에 의한 결함 검출 기법은 연구 대상 물체의 경우 결함 유무를 완벽하게 판정할 수 있었으며, 차후 유사한 형태의 구조물에 대한 결함 검출에도 응용될 수 있다.

• 한국정밀공학회지
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• 제17권4호
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• pp.240-246
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• 2000

An in-process estimation of the ground surface roughness is a bottle-neck and an essential field in conventional grinding operation. We defined the dimensionless average roughness factor (D.A.R.F) that exhibits a roughness characteristics of ground surface. The D.A.R.F was composed easily of the absolute average and the standard deviation values which were the analytic parameters of the acoustic emission (AE) signal generated during the machining process. The theoretical equation between the surface roughness and the D.A.R.F has been derived from the linear regressive analysis and verified its availability through the experimentation on the surface grinding machine.

• 한국산업융합학회 논문집
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• 제2권2호
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• pp.147-153
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• 1999

An in-process extraction method of the ground surface roughness is a bottle-neck and essential field in conventional machining process. We define the D.A.R.F(Dimensionless Average Roughness Factor) that has a roughness characteristic of ground surface. D.A.R.F include the absolute average and the standard deviation values which are the analytic parameters of the AE(Acoustic Emission) signal generated during the grinding operation. The theoretical equation between the surface roughness and the D.A.R.F has been derived from the linear regressive analysis and verified its availability through the experimentation on the surface grinding machine.

• 한국소음진동공학회논문집
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• 제17권8호
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• pp.693-700
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• 2007

We can predict spatial acoustic pressure distribution on the plane of interest by using acoustic holography. However, the information embedded in the distribution plot is usually much more than what we need: for example, source locations and their overall propagation pattern. One possible candidate to solve the problem is complex envelope analysis. Complex envelope analysis extracts slowly-varying envelope signal from a band signal. We have attempted to extend this method to space domain so that we can have spatial information that we need. We have to modulate two dimensional data for obtaining spatial envelope. Although spatial modulation basically follows the same concept that is used in time domain, the algorithm for the spatial modulation turns out to be different from temporal modulation. We briefly describe temporal complex envelope analysis and extend it to spatial envelope of 2-D acoustic field by introducing geometric transformation. In the end, the results of applying the spatial envelope to the holography are envisaged and verified.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.904-907
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• 2002

Optical disk drive device is improved in rotating speed for faster data reading. In the case of CD-ROM, rotating speed is over 10000 rpm in the practical use. As a result of high rotating speed, unexpected effects as like increasing disk fluctuation and acoustic noise are raised by the air friction on the rotating disk and the eccentricity of rotating parts. The overall acoustic noise of running CD-ROM could be classified into two different characterized noise. The first is the structural-borne noise which is generated from vibrating solid body. By the reason, the signal of structural borne noise has very similar to the signal of surface vibrating one. It has dense noise energy at specific frequency region. The other is the air-borne noise which is generated from turbulence or vortex caused by friction between disk and air. The signal of air-borne noise has no dominant peak point at acoustic pressure-frequency domain. The noise energy is widely distributed while comparatively high and large frequency region. The structural-borne noise could be reduced by reducing vibration of structure and in addition it's target reducing frequency is narrow. However the air-borne noise reduction is effectively needed of enclosing method for the noise source located near the disk surface because it is difficult to define target frequency point. In this study, the acoustic noise at driving CD-ROM is classified by the sides of it's character and tried to reduce the overall acoustic noise.

• 한국소음진동공학회논문집
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• 제16권7호
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• pp.729-738
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• 2006

Knowledge of acoustic transmission loss of acoustic window material has a great importance for the sonar performance in ship. The purpose of this study was to investigate the measurement and analysis method for the acoustic transmission loss of the acoustic window materials for sonar dome. The measurement and analysis were carried out in water with GRP material. Transmission losses were calculated based on integrated direct and transmitted signals. The experimental setup enabled to vary the angle of incidence. Thus the transmission loss data could be expressed as the function of frequency and angle of rotation. In this paper, diffraction effect of incident angle, size of specimen with test material, transmission analysis method and multiple waves as incident acoustic signal were discussed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.1183-1189
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• 2006

Knowledge of acoustic transmission loss of acoustic window material has a great Importance for the sonar performance in ship. The purpose of This study was to investigate the measurement and analysis method for me acoustic transmission loss of the acoustic window materials for sonar dome. The measurement and analysis were carried out in water with GRP material. Transmission losses were calculated based on integrated direct and transmitted signals. The experimental setup enabled to vary the angle of incidence. Thus the transmission loss data could be expressed as the function of frequency and angle of rotation. In this paper, diffraction effect of incident angle, size of specimen with test material, transmission analysis method and multiple waves as incident acoustic signal wet-e discussed

• 전기학회논문지
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• 제57권5호
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• pp.881-888
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• 2008

We present a novel fault diagnosis methodology using acoustic sensor systems and neural independent component analysis for large-scaled power machines. Acoustic sensors are carried out to measure sounds generated from power machines whose signal is used to determine whether fault is occurred or not. Acoustic measurements are independently mixed and deteriorated from original source signals. We propose a demixing algorithm against such mixed signals by means of independent component analysis which is achieved based on information theory and higher-order statistics to derive learning mechanism.