• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.1-11
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• 2000

This paper proposes the practical echo-signal synthesis models - UTAHID (Underwater TArget by Highlight Distribution) & M-UTAHID(Modified UTAHID) - of underwater target for active sonar engineering At high frequencies all the echo components that are the specular reflected waves and various elastic scattering wave scan be regarded the summation of individual echo from some equivalent scattering centers, so the underwater target is characterized by highlights distributed in spatial target structure. Proposed models are compared with characteristics of random distributed model & equivalent interval highlight model, and analyzed target strength, echo-elongation effect, target time spread loss and so on. Thus these can be efficiently used in various real systems related to underwater target echo-signal synthesis on active sonar and acoustic countermeasure.

• Journal of Ocean Engineering and Technology
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• v.13 no.3 s.33
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• pp.36-48
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• 1999

Fatigue life and crack retardation behavior after penetration were experimentally examined using surface pre-cracked specimens of aluminium alloy 5083. The Wheeler model retardation parameter was used successfully to predict crack growth behavior after penetration. By using a crack propagation rule, the change in crack shape after penetration can be evaluated quantitatively. Advanced, waveform-based acoustic emission (AE) techniques have been successfully used to evaluate signal characteristics obtained form fatigue crack propagation and penetratin behavior in 6061 aluminum plate with surface crack under fatigue stress. Surface defects in the structural members are apt to be origins of fatigue crack growth, which may cause serious failure of the whole structure. The nondestructive analysis on the crack growth and penetration from these defects may, therefore, be one of the most important subjects on the reliability of the leak before break (LBB) design. The goal of the present study is to determine if different sources of the AE could be identified by characteristics of the waveforms produced from the crack growth and penetration. AE signals detected in four stages were found to have different signal per stage. With analysis of waveform and power spectrum in 6061 aluminum alloys with a surface crack, it is found to be capabilities on real-time monitoring for the crack propagation and penetration behavior of various damages and defects in structural members.

• Phonetics and Speech Sciences
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• v.8 no.3
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• pp.31-38
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• 2016

Speech inversion (acoustic-to-articulatory mapping) is not a trivial problem, despite the importance, due to the highly non-linear and non-unique nature. This study aimed to investigate the performance of Deep Neural Network (DNN) compared to that of traditional Artificial Neural Network (ANN) to address the problem. The Wisconsin X-ray Microbeam Database was employed and the acoustic signal and articulatory pellet information were the input and output in the models. Results showed that the performance of ANN deteriorated as the number of hidden layers increased. In contrast, DNN showed lower and more stable RMS even up to 10 deep hidden layers, suggesting that DNN is capable of learning acoustic-articulatory inversion mapping more efficiently than ANN.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.3
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• pp.36-43
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• 2003

Multi-target away signal simulator which can simulate the radiated noises of maneuvering targets in a specified ocean range is an essential equipment for the validation of developed towed array sonar system. This simulator should provide realistic multi-channel signals those are required for beamforming on the signal processing unit of towed away system. This paper describes the overall system configuration and signal synthesis techniques for the target radiated noise. And this paper considers why the time delays between target and individual sensors are caused and how to compensate these time delays to individual sensors output. This multi-purpose target simulator could be used for the training of TASS operators.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.33-37
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• 2002

Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.121-128
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• 2017

In this paper, we propose a dual-channel acoustic event detection (AED) method using nonnegative tensor factorization (NTF) and hidden Markov model (HMM) in order to improve detection accuracy of AED in multisource environments. The proposed method first detects multiple acoustic events by utilizing channel gains obtained from the NTF technique applied to dual-channel input signals. After that, an HMM-based likelihood ratio test is carried out to verify the detected events by using channel gains. The detection accuracy of the proposed method is measured by F-measures under 9 different multisource conditions. Then, it is also compared with those of conventional AED methods such as Gaussian mixture model and nonnegative matrix factorization. It is shown from the experiments that the proposed method outperforms the convectional methods under all the multisource conditions.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.273-281
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• 2022

In this paper, we propose a robot sound recognition system that detects various sound events. The proposed system is designed to detect various sound events in real-time by using a microphone on a robot. To get real-time performance, we use a VGG11 model which includes several convolutional neural networks with real-time normalization scheme. The VGG11 model is trained on augmented DB through 24 kinds of various environments (12 reverberation times and 2 signal to noise ratios). Additionally, based on random forest algorithm, a decision logic is also designed to generate event signals for robot applications. This logic can be used for specific classes of acoustic events with better performance than just using outputs of network model. With some experimental results, the performance of proposed sound recognition system is shown on real-time device for robots.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.48 no.2
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• pp.233-243
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• 2015

Controlled broadband acoustic scattering laboratory experiments were conducted using a linear chirp signal (95-220 kHz), and x-ray images of live and model fish with an artificial swim bladder were analyzed to investigate the changes in orientation and frequency dependence of target strength (TS) due to morphological differences in fish swim bladders. The broadband echoes from live and model fish were measured over an orientation angle range of ${\pm}45^{\circ}$ in the dorsal plane and in approximately $1^{\circ}$ increments. The location of nulls in the simulated echo response of the SINC [sinc function] model was overlaid on the TS map, showing the orientation and frequency dependence of fish TS, and they matched very well. It was possible to infer the equivalent fish scattering size (or swim bladder) using the null spacing in the experimentally obtained broadband TS map. Good agreement was observed for inferring the equivalent scattering size between the SINC model and the broadband echoes measured for the three fish species (black scraper Thamnaconus modestus; goldeye rockfish Sebastes thompsoni; and whitesaddled reef fish Chromis notatus). Some results of this inference are discussed.

• The KSFM Journal of Fluid Machinery
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• v.3 no.2 s.7
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• pp.15-23
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• 2000

The present work describes the prediction method for the unsteady flow field and the acoustic pressure field of a ducted axial fan. The prediction method is comprised of time-marching free-wake method, acoustic analogy, and the Kirchhoff-Helmholtz BEM. The predicted sound signal of a rotor is similar to the experiment one. We assume that the rotor rotates with a constant angular velocity and the flow field around the rotor is incompressible and inviscid. Then, a time-marching free-wake method is used to model the fan and to calculate the flow field. The force of each element on the blade is calculated by the unsteady Bernoulli equation. Lowson's method is used to predict the acoustic source. The newly developed Helmholtz-Kirchhoff BEM lot thin body is used to calculate tile sound field of the ducted fan. The ducted fan with 6 blades is analysed and the sound field around the duct is calculated.