• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.216-225
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• 2020

In this paper, broadband underwater propagation channel modeling based on eigenray analysis is discussed. Underwater channels are often formulated in frequency domain time-harmonic signals, which are impractical for simulating broadband signals in time domain. In this regard, time domain modeling of the underwater propagation channel is required for the simulation of broadband signals, for which the eigenray analysis based on ray tracing, resulting in multipath propagation delays in time-domain, is used in this paper. For discrete time system application, the phase, frequency-dependent loss and non-integer sample delays for each eigenray, are approximated by the finite impulse response of the broadband propagation channel.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.6
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• pp.35-42
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• 2000

In this paper, AE(Acoustic Emission) signals detected from the growth of the electrical tree in an epoxy resin under ac high-voltage application were analysed to diagnose the insulation deterioration of cast-resin power transformer. Frequency spectra of AE signals generated from the magnetizing and the load currents in the actual operating cast-resin power transformer of 500[kVA] under distribution system of 22.9[kV] were also analysed to distinguish the AE signals due to void discharges from the magnetic circuit noises in the core of the transformer. As the experimental results, we could distinguish the AE signals whether those signals were caused due to the void discharges or due to the magnetic circuit noises by analyzing the frequency spectrum of AE signals. The frequency spectra of AE signals generated from the cast-resin power transformer in operation due to both the magnetizing and the load currents appeared in the range of 40-120[kHz], but the frequency band of AE signals emitted from the void discharges in an epoxy resin sample was about 50[kHz] to 230[kHz].

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.403-409
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• 2016

Traditional towed line arrays using omni-directional sensor suffer from the well known port-starboard ambiguity, because the direction of arrival is determined by conic angle. The operational method and structure of the sensor arrays method have been proposed to solve this problem. Recently, a lot of research relating to the acoustic vector sensor are studied. In this paper, we study port-starboard discrimination for roll of acoustic vector sensor array. With one omni-directional sensor and three orthogonally-placed directional sensors, an acoustic vector sensor is able to measure both the acoustic pressure and the three directional velocities at the point of the sensor. The wrong axis due to the roll at directional sensors can degrade performance of beamforming. We investigate port-starboard discrimination for roll of sensor array and confirm the validity of performance of beamforming with compensated the roll.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.412-421
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• 2018

The Line array sonar consisting of several hydrophones increases array gain and improves the performance for detecting the direction of the target compared to single hydrophone. However, line array sonar produces the bearing error that makes it difficult to determine the bearing of incoming source signal due to the relation between bearing angle of target and vertical angle of multipath signals. Vertical angles of multipath are varied with the geometry of receiver and target and various underwater environments, therefore it is necessary to consider the bearing error to estimate accurately the bearing of the target. In this study, acoustic modelling was performed to understand the effect of multipath signals on the target signal. The errors of bearing angle estimated from the bottom bounced signals are calculated with several environment. In addition, the expected bearing line, as a function of source-receiver range, compensated for the bearing error is predicted from the estimated bearing angle.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.496-503
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• 2010

Speech recognition system is developed of standalone, In case of a mobile terminal using that low recognition rate represent because of limitation of memory size and audio compression. This study suggest vocabulary recognition highest performance improvement system for separate acoustic search and lexical search. Acoustic search is carry out in mobile terminal, lexical search is carry out in server processing system. feature vector of speech signal extract using GMM a phoneme execution, recognition a phoneme list transmission server using Lexical Tree Search algorithm lexical search recognition execution. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.71%, represent recognition speed of 1.58 second.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.169-173
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• 2021

Currently, safety accidents in hospitals are steadily occurring. In particular, safety accidents of elderly patients with weak immunity, such as nursing hospitals, continue to occur, and countermeasures are needed. Most accidents are caused by patient movement. As a method of reducing safety accidents by analyzing and recognizing the sound of the inpatient room according to the movement of the patient, this paper classifies the sound pattern for sound recognition in the hospital inpatient room using DTW (Dynamic Time Warping), an algorithm applicable to time-series pattern recognition. It was analyzed by applying it to the inpatient room environment.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.4
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• pp.1-9
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• 2022

In the current study, in order to understand the dynamic response characteristics of the system according to the external acoustic forcing, a numerical approach was developed by adding an sign-sweep forcing function to the existing network model. Through this model, the sensitivity of frequency and pressure amplitude changes according to system parameters such as the physical dimensions and boundary conditions of the target combustor was analyzed in a wide frequency range. Analysis results of dynamic response characteristics of the target combustor are shown that the frequency regime with high dynamic pressure response was similar to the instability frequency range measured in the same combustor, and in particular, the response of the system depends greatly on the location of the acoustic forcing source term.

• The Journal of the Acoustical Society of Korea
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• v.14 no.5
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• pp.5-10
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• 1995

In this paper we present a clustering procedure based on the use of HMM in order to get multiple statistical models which can well absorb the variants of each speaker with different ways of saying words. The HMM-clustered models obtained from the developed technique are applied to the speaker independent isolated word recognition. The HMM clustering method splits off all observation sequences with poor likelihood scores which fall below threshold from the training set and create a new model out of the observation sequences in the new cluster. Clustering is iterated by classifying each observation sequence as belonging to the cluster whose model has the maximum likelihood score. If any clutter has changed from the previous iteration the model in that cluster is reestimated by using the Baum-Welch reestimation procedure. Therefore, this method is more efficient than the conventional template-based clustering technique due to the integration capability of the clustering procedure and the parameter estimation. Experimental data show that the HMM-based clustering procedure leads to $1.43\%$ performance improvements over the conventional template-based clustering method and $2.08\%$ improvements over the single HMM method for the case of recognition of the isolated korean digits.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.177-183
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• 2019

In this paper, we proposed an application method of ICA (Independent Component Analysis) to passive line array sonar to separate interferences from target signals in low frequency band and compared performance of three conventional ICA algorithms. Since the low frequency signals are received through larger bearing angles than other frequency bands, neighboring beam signals can be used to perform ICA as measurement signals of the ICA. We use three ICA algorithms such as Fast ICA, NNMF (Non-negative Matrix Factorization) and JADE (Joint Approximation Diagonalization of Eigen-matrices). Through experiments on real data obtained from passive line array sonar, it is verified that the interference can be separable from target signals by the suggested method and the JADE algorithm shows the best separation performance among the three algorithms.