• The Journal of the Acoustical Society of Korea
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• v.37 no.2
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• pp.118-128
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• 2018

In this paper, we have studied how to search an underwater object by learning the image generated by the side scan sonar in the convolution neural network. In the method of human side analysis of the side scan image or the image, the convolution neural network algorithm can enhance the efficiency of the analysis. The image data of the side scan sonar used in the experiment is the public data of NSWC (Naval Surface Warfare Center) and consists of four kinds of synthetic underwater objects. The convolutional neural network algorithm is based on Faster R-CNN (Region based Convolutional Neural Networks) learning based on region of interest and the details of the neural network are self-organized to fit the data we have. The results of the study were compared with a precision-recall curve, and we investigated the applicability of underwater object detection in convolution neural networks by examining the effect of change of region of interest assigned to sonar image data on detection performance.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.263-269
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• 2020

In this study, a rotating machine that can reproduce normal condition and 8 fault conditions were produced, and vibration data was acquired. Feature is calculated from the acquired data, and accuracy is analyzed through fault diagnosis using artificial neural networks and genetic algorithms. In order to achieve optimal timing and higher accuracy, features by three domains were applied to the fault diagnosis. The learning number was selected as a setting variable. As a result of the rotating machine fault diagnosis, high precision was found in the frequency domain than in others, and precise fault diagnoses were accomplished through all of 10 operations, at the learning number of 5000 and 8000. Given the efficiency of time, it was estimated to be the most efficient when the number of learning was 5000.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.246-254
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• 2020

In this paper, we propose a learning based compressive sensing algorithm for the purpose of side scan sonar image denoising. The proposed method is based on Iterative Shrinkage and Thresholding Algorithm (ISTA) framework and incorporates a powerful strategy that reinforces the non-linearity of deep learning network for improved performance. The proposed method consists of three essential modules. The first module consists of a non-linear transform for input and initialization while the second module contains the ISTA block that maps the input features to sparse space and performs inverse transform. The third module is to transform from non-linear feature space to pixel space. Superiority in noise removal and memory efficiency of the proposed method is verified through various experiments.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.279-285
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• 2020

The study on the temporal and spatial monitoring of passing vessels is important in terms of protection and management the marine ecosystem in the coastal area. In this paper, we propose the automatic detection technique of passing vessel by utilizing an artificial intelligence technology and broadband striation patterns which are characteristic of broadband noise radiated by passing vessel. Acoustic measurements to collect underwater noise spectrum images and ship navigation information were conducted in the southern region of Jeju Island in South Korea for 12 days (2016.07.15-07.26). And the convolution neural network model is optimized through learning and validation processes based on the collected images. The automatic detection performance of passing vessel is evaluated by precision (0.936), recall (0.830), average precision (0.824), and accuracy (0.949). In conclusion, the possibility of the automatic detection technique of passing vessel is confirmed by using an artificial intelligence technology, and a future study is proposed from the results of this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.978-983
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• 2010

Acoustic target classification in wireless sensor network is important research at environmental surveillance, invasion surveillance, multiple target separation. General sensor node signal processing methods concentrated on received signal energy based target detection and received raw signal compression. The former is not suited to target classification because of almost every target information are lost except target energy. The latter bring down life-time of sensor node owing to high computational complexity and transmission energy. In this paper, we introduce an feature extraction algorithm for acoustic target classification in wireless sensor network which has time and frequency information. The proposed method extracts time information and de-noised target classification information using wavelet decomposition step. This method reduces communication energy by 28% of original signal and computational complexity.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.180-180
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• 2012

ADCP는 3차원 유속과 수심을 관측하여 유량을 정확하게 계산하는 데 널리 이용되고 있는 최신계측기기로 국내에서도 유량조사사업단 등 기관에 도입되어 수위-유량관계곡선식의 보정 등에 적용되고 있다. 하지만 ADCP 관측값 중 수심관측 자료를 별도로 활용하는 부분도 많은 관심을 받고 있다. 특히 최근 4대강 사업으로 인한 하상변동 측정에 기존 유량관측용으로 구매된 ADCP를 수심관측용으로 활용할 수 있다. ADCP는 일정한 각도로 경사진 4개의 초음파 빔을 활용하여 사선 방향으로 수심을 각각 관측한다. 최근에는 별도의 수심관측용의 수직 빔을 추가 설치하여 한번 관측에 초당 5개 지점의 수심을 동시에 관측할 수 있어 수심관측용으로도 기존 단독빔 음향측심기에 비해 효율적으로 수심을 관측할 수 있다. 그리고 ADCP는 GPS와 연동되어 수심관측의 3차원 공간정보 (x, y, z)를 창출할 수 있어 기존 GIS 자료와 융합될 수 있다. 하지만 기존의 음향 측심기의 수직빔과 다르게 ADCP의 빔이 일정한 각도로 경사져 있고 선박 활용 관측 시 요동에 의해 흔들려 각각의 빔이 계측한 수심의 수평위치를 정확하게 추출하기 어려운 점이 있다. 특히 경사빔에 의한 수심관측지점에 GPS 정보를 추정하여 부여하는 작업도 까다롭다고 하겠다. 그리고 수심관측자료 자체의 오차나 특이점 제거 등의 보정작업을 거쳐야 하는 문제도 있다. 따라서 원자료를 직접 활용할 수 없고 별도의 후처리 과정을 거쳐야 한다. 따라서 본 연구는 이러한 문제를 해결하기 위해 다음의 알고리즘을 개발하였다: 1) 경사빔에 의한 관측지점의 수평위치 산정, 2) ADCP의 흔들림 (피치와 롤링) 보정, 3) 경사빔의 관측위치에 지리정보부여, 4) 수심관측치 오차와 특이점 보정, 5) 관측자료의 GIS 파일 전환. 이러한 알고리즘은 GUI와 연동되어 적용되었으며 편리하게 이용되도록 구성되었다. 그리고 본 연구는 이러한 ADCP의 수심관측 자료와 하천 및 저수지 등 경계 GIS 파일을 연동시켜 전체 혹은 국부 저수량과 하상변동량을 계상하는 알고리즘도 추가하여 관측자료의 실무에서의 활용성을 증대시키고자 하였다.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.270-277
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• 2021

In the power ultrasound fields, the flange position for fixing the transducer is an important factor influencing on electro-mechanical efficiency of the transducer. We suggested a practical method that can determine the installation position of the flange for different resonance modes of the bolt-clamped type Langevin ultrasonic transducer. A semicircular wedge-shaped jig was manufactured and moved along the lateral surface of the transducer. The vibration characteristics were examined after a constant pressure was applied to the semicircular wedge-shaped jig. By observing the change of the input admittance of the transducer depending on the position of the pressure application, the optimum position for the flange installation could be determined. The resonant modes of the transducer were calculated by a Mason's equivalent circuit, and the particle velocity distribution for each resonance mode was calculated by a transmission line model. Since the optimum positions determined from an experimental result show a good correspondence with the node positions of the vibration modes calculated by the transmission line model, the validity of the suggested method was verified.

• Geophysics and Geophysical Exploration
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• v.22 no.2
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• pp.56-61
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• 2019

In this paper, we studied efficient modeling strategies when we simulate the 3D time-domain acoustic wave propagation using a cell-based finite difference method which can handle the variations of both P-wave velocity and density. The standard finite difference method assigns physical properties such as velocities of elastic waves and density to grid points; on the other hand, the cell-based finite difference method assigns physical properties to cells between grid points. The cell-based finite difference method uses average physical properties of adjacent cells to calculate the finite difference equation centered at a grid point. This feature increases the computational cost of the cell-based finite difference method compared to the standard finite different method. In this study, we used additional memory to mitigate the computational overburden and thus reduced the calculation time by more than 30 %. Furthermore, we were able to enhance the performance of the modeling on several media with limited density variations by using the cell-based and standard finite difference methods together.

• The Journal of the Acoustical Society of Korea
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• v.40 no.1
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• pp.10-17
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• 2021

The cymbal transducer is a miniaturized version of the Class V flextensional transducer. It has low resonant frequency and high output pressure characteristics compared with its size. However, since it has high quality factor and low energy conversion efficiency as well, it is often used as an array rather than single. When used as an array, a big change in the frequency characteristics occurs in comparison with that of the single transducer due to the interaction between constituent transducers. In this study, we designed a pattern of cymbal array with a view to having broadband characteristics. Three transducers having different center frequencies were designed first. The designed cymbal transducers were used to construct all possible patterns of a 3 × 3 planar array. After analyzing frequency characteristics of these patterns, based on the results, we derived the most effective pattern to achieve a higher fractional bandwidth. The derived array pattern showed an improvement of the fractional bandwidth by 24.9 % in comparison with the reference model.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.501-506
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• 2022

Echogenic liposome contains both liquid and gas inside the shell. In ultrasound mediated drug delivery, sonoporation, these new microbubbles can be an attractive drug carrier since they can be loaded water soluble drugs and drug molecules can be unloaded at the specific location with ultrasound sonication. In this paper, the structure of the echogenic liposome was confirmed with EF-TEM and the positive effect of sonoporation with echogenic liposome was comparatively evaluated on MDA-MB-231 cells which is a type of breast cancer cell with Doxorubicin. Control group (Group 1), Doxorubicin only (Group 2), sonoporation with Doxorubicin and hollow microbubbles (Group 3), sonoporation with Doxorubicin loaded echogenic liposome (Group 4) were classified and experiments were conducted. According to the results, Group 4 is at least 1.4 times better in inducing necrosis of cancer cells. Therefore, we conclude echogenic liposome could be one of the most useful form of microbubbles in sonoporation.