• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.2
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• pp.224-233
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• 2016

The objective of this study was to develop an artificial neural network (ANN) model for the acoustic identification of commercially important fish species in Korea. A broadband echo acquisition and processing system operating over the frequency range of 85-225 kHz was used to collect and process species-specific, time-frequency feature images from six fish species: black rockfish Sebastes schlegeli, black scraper Thamnaconus modesutus [K], chub mackerel Scomber japonicus, goldeye rockfish Sebastes thompsoni, konoshiro gizzard shad Konosirus punctatus and large yellow croaker Larimichthys crocea. An ANN classifier was developed to identify fish species acoustically on the basis of only 100 dimension time-frequency features extracted by the principal components analysis (PCA). The overall mean identification rate for the six fish species was 88.5%, with individual identification rates of 76.6% for black rockfish, 82.8% for black scraper, 93.8% for chub mackerel, 90.6% for goldeye rockfish, 96.9% for konoshiro gizzard shad and 90.6% for large yellow croaker, respectively. These results demonstrate that individual live fish in well-controlled environments can be identified accurately by the proposed ANN model.

• MALSORI
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• no.40
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• pp.1-12
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• 2000

This paper investigated how $/\int/$ in English and German is perceived and interpreted in the loanwords in Korean. $/\int/$ in these languages does not show one-to-one correspondence in Korean: $/\int/$ in the coda position in English and German is perceived as [swi] in Korean while $/\int/$ in the onset position is perceived as [syu]. This paper examined phonetic characteristics of $/\int/$ in English and German through its acoustic analysis and attempted to figure out which factor could explain this surface distribution of [swi] and [syu]; phonological (onset vs. coda) or phonetic (coarticulation) factor. Two acoustic features of $/\int/$ in English and German were examined: duration and energy Peak frequency of the frication noise. German $/\int/$ Perceived as [swi] in Korean showed higher energy Peak frequency and longer duration than that perceived as [syu] in Korean. English iii perceived as [swi] also showed longer duration than that Perceived as [syu] in Korean but energy Peak frequency showed different behavior. English $/\int/$ showed coarticulation with the preceding vowel rather than being affected by its position in the syllable in English. This paper concludes that 1)Phonetic characteristics used are duration and energy Peak frequency of its frication noise when $/\int/$ in English and German are adopted in Korean, 2)duration is used prior to energy peak frequency, which can be used as an enhancing feature.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.185-190
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• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.6
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• pp.795-801
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• 1999

An experimental investigation has been conducted with the objective of studying the mixing mechanism near the nozzle exit in a tone-excited jet diffusion flame. The fuel jet was pulsed by means of a loudspeaker-driven cavity. The excitation frequencies were chosen for the two cases of the non-resonant and resonant frequency identified as a fuel tube resonance due to acoustic excitation. The effect of tone-excitations on mixing pattern near the nozzle exit and flame was visualized using various techniques, including schlieren photograph and laser light scattering photograph from $TiO_2$ seed particles. In order to clarify the details of the flame feature observed by visualization methods, hotwire measurements have been made. Excitation at the resonant frequency makes strong mixing near the nozzle. In this case, the fuel jet flow in the vicinity of nozzle exit breaks up into disturbed fuel parcels. This phenomena affects greatly the combustion characteristics of the tone excited jet and presumably occurs by flow separation from the wall inside the fuel nozzle. As a result, in the resonant frequency the flame length reduces greatly.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.54-65
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• 1998

This study attempts to test the classifying performance of a neural network and thereby examine its applicability to the signals distorted in a shallow water environment. Linear frequency modulated(LFM) signals are simulated by using an acoustic model and also measured through sea experiment. The network is constructed to have three layers and trained on both data sets. To get normalized power spectra as feature vectors, the study considers the three transforms : shot-time Fourier transform (STFT), wavelet transform (WT) and pseudo Wigner-Ville distribution (PWVD). After trained on the simulated signals over water depth, the network gives over 95% performance with the signal to noise ratio (SNR) being up to-10 dB. Among the transforms, the PWVD presents the best performance particularly in a highly noisy condition. The network performs worse with the summer sound speed profile than with the winter profile. It is also expected to present much different performance by the variation of bottom property. When the network is trained on the measured signals, it gives a little better results than that trained on the simulated data. In conclusion, the simulated signals are successfully applied to training a network, and the trained network performs well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1880-1884
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• 2000

The discrete wavelet transform is utilized as preprocessing of Neural Network(NN) to identify aging state of internal partial discharge in transformer. The discrete traveler transform is used to produce wavelet coefficients which are used for Classification. The statistical parameters (maximum of wavelet coefficients, average value, dispersion, skewness, kurtosis) using the wavelet coefficients are input into an back-propagation neural network. The neurons whose weights have obtained through Result of Cross-Validation. The Neural Network learning stops either when the error rate achieves an appropriate minimum or when the learning time overcomes a constant value. The networks, after training, can decide if the test signal is Early Aging State or Last Aging State or normal state.

• ETRI Journal
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• v.42 no.5
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• pp.761-772
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• 2020

This paper presents an automatic proficiency assessment method for a non-native Korean read utterance using bidirectional long short-term memory (BLSTM)-based acoustic models (AMs) and speech data augmentation techniques. Specifically, the proposed method considers two scenarios, with and without prompted text. The proposed method with the prompted text performs (a) a speech feature extraction step, (b) a forced-alignment step using a native AM and non-native AM, and (c) a linear regression-based proficiency scoring step for the five proficiency scores. Meanwhile, the proposed method without the prompted text additionally performs Korean speech recognition and a subword un-segmentation for the missing text. The experimental results indicate that the proposed method with prompted text improves the performance for all scores when compared to a method employing conventional AMs. In addition, the proposed method without the prompted text has a fluency score performance comparable to that of the method with prompted text.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2511-2514
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• 2008

As the minimum feature size decreases, techniques to avoid contamination and processes to maintain clean wafer surfaces have become very important. The deposition and detachment of nanoparticles from surfaces are major problem to integrated circuit fabrication. Therefore, cleaning technology which reduces nanoparticles is essential to increase yield. Previous megasonic cleaning technology has reached the limits to reduce nanoparticles. Megasonic cleaning is one of the efficiency method to reduce contamination nanoparticle. Two major mechanisms are active in a megasonic cleaning, namely, acoustic streaming and cavitation. Acoustic streaming does not lead to sufficiently strong force to cause damage to the substrates or patterns. Sonoluminescence is a phenomenon of light emission associated with the cavitation of a bubble under ultrasound. We studied a correlation between sonoluminescence and sound pressure distribution for the minimum of pattern damage in megasonic cleaning.

• Smart Structures and Systems
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• v.21 no.4
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• pp.421-433
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• 2018

Carbon fiber reinforced polymer (CFRP) cable has good mechanical properties and corrosion resistance. However, the anchorage of CFRP cable is a big issue due to the anisotropic property of CFRP material. In this article, a high-efficient bonding anchorage with novel configuration is developed for CFRP cables. The acoustic emission (AE) technique is employed to evaluate the performance of anchorage in the fatigue test and post-fatigue ultimate bearing capacity test. The obtained AE signals are analyzed by using a combination of unsupervised K-means clustering and supervised K-nearest neighbor classification (K-NN) for quantifying the performance of the anchorage and damage evolutions. An AE feature vector (including both frequency and energy characteristics of AE signal) for clustering analysis is proposed and the under-sampling approaches are employed to regress the influence of the imbalanced classes distribution in AE dataset for improving clustering quality. The results indicate that four classes exist in AE dataset, which correspond to the shear deformation of potting compound, matrix cracking, fiber-matrix debonding and fiber fracture in CFRP bars. The AE intensity released by the deformation of potting compound is very slight during the whole loading process and no obvious premature damage observed in CFRP bars aroused by anchorage effect at relative low stress level, indicating the anchorage configuration in this study is reliable.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.1
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• pp.47-52
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• 2011

An electromagnetic acoustic transducer(EMAT) is a non-contact transducer which can transmit the ultrasonic guided waves into specimens without couplant. And it can easily generate specific guided waves such as SH(shear horizontal) or Lamb waves by altering the design of coil and magnet. In this study, the SH wave, which is generated by EMAT, has been applied to estimate the thickness-reduction in a steel plate. Especially, the interesting feature of the dispersive behavior in selected wave modes is used to detect the thickness-reduction. Experimental results show that the reduction-level can be quantified by the measurement of the group velocity of the wave which passes though the thinning area.