• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.110-117
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• 2016

Passive sonar systems detect and classify the target by analyzing the radiated noises from vessels. If multiple noise sources exist within the sonar detection range, it gets difficult to classify each noise source because mixture of noise sources are observed. To overcome this problem, a beamforming technique is used to separate noise sources spatially though it has various limitations. In this paper, we propose a new method that uses a FDICA (Frequency Domain Independent Component Analysis) to separate noise sources from the mixture. For experiments, each noise source signal was synthesized by considering the features such as machinery tonal components and propeller tonal components. And the results of before and after separation were compared by using LOFAR (Low Frequency Analysis and Recording), DEMON (Detection Envelope Modulation On Noise) analysis.

• Journal of KSNVE
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• v.7 no.2
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• pp.255-260
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• 1997

This paper describes 3-dimensional volume array of 4 microphones including a reference microphone which is capable of imaging wideband noise source position in 2-dimensional image plane. The cross correlation function and corresponding imaging function between a reference microphone and other microphone, are derived as a function of noise source position. The magnitude of the imaging function gives noise source mapping in image plane. Since the image plane is selective from a rectangular and a cylindrical plane, noise source position information such as range and bearing relative to the array is identified very much easily. Simulation results for typical source configurations confirms the applicability of the proposed array in noise control field.

• Journal of KSNVE
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• v.6 no.6
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• pp.835-842
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• 1996

To identify the locations and strengths of acoustic sources, one may use a microphone line array. Apparent advantage of the source identification method utilizing a line array is that it requires less measurement points than intensity method and holography. This method is based on the information of magnitude and phase difference between pressure signals at each microphone. Since those differences are dependent on the source model, we have to assume them such as plane, monopole, etc. In this paper the conventional source identification methods such as beamforming method and MUSIC method are briefly reviewed by modeling a source as plane and spherical wave, then a modified method is introduced. This can be applied to sound field which may by either coherent or incoherent. Typical simulations and experiment are performed to confirm this identification method.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.289-292
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• 1999

다수의 마이크로폰 어레이를 사용하여 소음원에서 방사하는 음장을 예측, 가시화하고 소음원의 시, 공간적 특성을 파악하기 위하여 음향 홀로그래피 방법에 대한 연구를 수행하였다. 음향 홀로그래피 방법은 실험적으로 소음원의 특성을 규명할 수 있기 때문에 많은 연구가 활발히 진행되고 있지만, 많은 개수의 마이크로폰과 신호수집장치 등이 필요하기 때문에 그 사용에 많은 제약이 있어 왔다. 음향 홀로그래피 방법중에서 대표적인 평면 음향 홀로그래피 방법을 중심으로 마이크로폰의 개수, 간격등과 같은 측정조건과 함께 마이크로폰을 스캐닝하는 방법둥에 대한 해석을 통하여 장, 단점 및 제한성을 논하였다. 또한 이러한 측정방법에서 나타나는 오차요인을 해석하고 이를 보정하는 방법에 대한 설명과 함께 실험을 통하여 이를 확인해 보았다.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.606-614
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• 2020

In this paper, we analyze the influences of ship traffic and marine weather information on underwater ambient noise. Ambient noise is an important environmental factor that greatly affects the detection performance of underwater sonar systems. In order to implement an automated system such as prediction of detection performance using artificial intelligence technology, which has been recently studied, it is necessary to obtain and analyze major data related to these. The main sources of ambient noise have various causes. In the case of sonar systems operating in offshore seas, the detection performance is greatly affected by the noise caused by ship traffic and marine weather. Therefore, in this paper, the impact of each data was analyzed using the measurement results of ambient noise obtained in coastal area of the East Sea of Korea, and public data of nearby ship traffic and ocean weather information. As a result, it was observed that the underwater ambient noise was highly correlated with the change of the ship's traffic volume, and that marine environment factors such as wind speed, wave height, and rainfall had an effect on a specific frequency band.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.317-322
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• 1994

본 연구에서는 원통면 음향 홀로그래피 방법에 대한 세밀한 고찰을 통하여 이 방법을 이용한 음장예측의 실제 적용에 도움을 주고자 한다. 먼저 원통면 음향 홀로그래피 방법의 기본적인 이론에 대한 고찰을 하였고, 원통면 음향 홀로그래피 방법의 실제 적용시 나타나는 창문함수의 영향(window effect)이나 공간상의 엘리어싱(spatial aliasing), 둘러싸기 오차(wraparound error)와 같은 오차에 대하여 모의 실험을 통하여 살펴보았다. 이러한 오차해석을 통하여 가능한 한 오차를 줄이고 신뢰할 수 있는 예측결과를 얻을 수 있는 측정조건을 제시하였으며, 오차를 감소시킬수 있는 Tukey 창문함수의 사용과 제로패딩(zero padding) 방법을 제시하였다. 이러한 기본적인 이해를 바탕으로 원통형 구조물의 방사음장을 예측하는 실험을 하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1704-1709
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• 2000

This paper proposes a spherical probe allowing acoustic intensity measurements in three dimensions to be made, which creates a diffracted field that is well-defined, thanks to analytic solution of diffraction phenomena. Six microphones are distributed on the surface of the sphere along three rectangular axes. Its measurement technique is not based on finite difference approximation, as is the case for the ID probe but on the analytic solution of diffraction phenomena. In fact, the success of sound source identification depends on the inverse models used to estimate inverse diffraction phenomena, which has non-linear properties. In this paper, we introduce the concept of nonlinear inverse diffraction modeling using a neural network and the idea of 3 dimensional sound source identification with several tests.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.7
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• pp.520-526
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• 2002

Identification of noose sources, their locations and strengths, has been taken great attention. The methods that can identify noise sources normally assume that noise sources are located in a free field. However, the sound in a reverberant field consists of that coming directly from the source plus sound reflected or scattered by the walls or objects in the field. In contrast to the exterior sound field. reflections are added to sound field. Therefore, we haute to consider the reverberation effect on the source identification method. The main objective of this paper is to identify noise source in the reverberant field. At fist, we try to identify noise sources in a rigid wall emc;psire using the beamforming method. In many cases of practical interest, the wall has admittance so that random reflections occur in an enclosure. In this paper, we assumed the complex reverberant field in the enclosure to be the sum of plane caves with random Incidence and magnitude. Then we try to explain effects of reverberant field at interior source identification.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.7
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• pp.586-603
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• 2004

One of the subtle problems that make noise control difficult for engineers is “the invisibility of noise or sound.” The visual image of noise often helps to determine an appropriate means for noise control. There have been many attempts to fulfill this rather challenging objective. Theoretical or numerical means to visualize the sound field have been attempted and as a result, a great deal of progress has been accomplished, for example in the field of visualization of turbulent noise. However, most of the numerical methods are not quite ready to be applied practically to noise control issues. In the meantime, fast progress has made it possible instrumentally by using multiple microphones and fast signal processing systems, although these systems are not perfect but are useful. The state of the art system is recently available but still has many problematic issues : for example, how we can implement the visualized noise field. The constructed noise or sound picture always consists of bias and random errors, and consequently it is often difficult to determine the origin of the noise and the spatial shape of noise, as highlighted in the title. The first part of this paper introduces a brief history, which is associated with “sound visualization,” from Leonardo da Vinci's famous drawing on vortex street (Fig. 1) to modern acoustic holography and what has been accomplished by a line or surface array. The second part introduces the difficulties and the recent studies. These include de-Dopplerization and do-reverberation methods. The former is essential for visualizing a moving noise source, such as cars or trains. The latter relates to what produces noise in a room or closed space. Another mar issue associated this sound/noise visualization is whether or not Ivecan distinguish mutual dependence of noise in space : for example, we are asked to answer the question, “Can we see two birds singing or one bird with two beaks?"

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.320-324
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• 2013

A crack identification method using an equivalent bending stiffness for cracked beam and committee of neural networks is presented. The equivalent bending stiffness is constructed based on an energy method for a straight thin-walled pipe, which has a through-the-thickness crack, subjected to bending. Several numerical analysis for a steel cantilever pipe using the equivalent bending stiffness are carried out to extract the natural frequencies and mode shapes of the cracked beam. The extracted modal properties are used in constructing a training patterns of a neural network. The input to the neural network consists of the modal properties and the output is composed of the crack location and size. Multiple neural networks are constructed and each individual network is trained independently with different initial synaptic weights. Then, the estimated crack locations and sizes from different neural networks are averaged. Experimental crack detection is carried out for 3 damage cases using the proposed method, and the identified crack locations and sizes agree reasonably well with the exact values.