• Proceedings of the KSME Conference
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• 2000.04a
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• pp.67-72
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• 2000

Demand for now nondestructive evaluation are growing to detect fatigue crack growth behavior to predict long term performance of materials and structure in aggressive environments especially when they are In non-visible area. Acoustic emission technique is well suited to these problems and has drawn a keen interests because of its dynamic detection ability, extreme sensitivity and location of growing defects. In this study, we analysed acoustic emission signals obtained in fatigue and tensile test of high strength fire resistance steel for frame structure with time-frequency analysis methods. The main frequency range is different in the noise and the fatigue crack propagation. It could be classified that it were also generated by composite fracture mechanics of cleavage, dimple, inclusion separation etc.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.2
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• pp.147-152
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• 2012

This paper dealt with the frequency component analysis of acoustic signals produced by corona and series-arc discharges as a diagnostic technique for closed-switchboards. Corona and series-arc discharge were simulated by a needle-plane electrode and an arc generator specified in UL1699, respectively. Acoustic signal was detected by a wideband acoustic sensor with a frequency bandwidth of 4 Hz~100 kHz (-3 dB). We analyzed frequency spectrums of the acoustic signals detected in various discharge conditions. The results showed that acoustic signals mainly exist in ranges from 30 kHz to 60 kHz. From the experimental results, an acoustic detection system which consists of a constant current power supply (CCP), a low noise amplifier (LNA) and a band pass filter was designed and fabricated. The CCP separates the signal component from the DC source of acoustic sensor, and the LNA has a gain of 40 dB in ranges of 280 Hz~320 kHz. The high and the low cut-off frequency are 30 kHz and 60 kHz, respectively. We could detect corona and series-arc discharges without any interference by the acoustic detection system, and the best frequency is considered in ranges of 30 kHz~60 kHz.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1292-1297
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• 2004

Acoustic characteristics in an industrial gas-turbine combustor are numerically investigated by adopting linear acoustic analysis. Spatially non-homogeneous temperature field in the combustor is considered in the numerical calculation and the characteristics are analyzed in view of acoustic instability. Acoustic analysis are conducted in the combustors without and with acoustic resonator, which is one of combustion stabilization devices. It has been reported that severe pressure fluctuation frequently occurs in the adopted combustor, and the measured signal of pressure oscillation is compared with the acoustic-pressure response from the numerical calculation. The numerical results are in a good agreement with the measurement data. In this regard, the phenomenon of pressure fluctuation in the combustor could be caused by acoustic instability. The acoustic effects of the resonators are analyzed in the viewpoints of both the frequency tuning and the damping capacity.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.217-225
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• 2000

Scanning Acoustic Microscope (SAM) is used as an important nondestructive test tool in semiconductor reliability evaluation and failure analysis. However, inspections of chip attach adhesive interface fer thin chip has proven difficulty as the reflected signals from the chip top and bottom are superimposed. In this paper, in order to overcome this difficulty, a new signal processing method based on the deconvolution technique combined with the wavelet transform is proposed. The wavelet transform complements a disability of deconvolution technique of which performance largely decreases when the waveform of target signal is not identical to that of reference signal. Performances of the proposed method are demonstrated by through computer simulations using model signal and experiments for the fabricated semiconductor samples, and satisfactory results are obtained.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.468-472
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• 2000

This paper discusses the development of a acoustic vector channel simulator for the performance analysis of a acoustic digital communication system. The channel simulator consists of transmission module, acoustic channel model, receiver, beamformer, and adaptive equalizer. QPSK source signal is generated by the parameters specified by a user and transmitted. The transmitted signal generate multipath signals which have a different delay, amplitude, and dopper Sequency. The multipath signals with the acoustic noises is the received signal. We can analysis the communication system performance according to the antenna structure, beamforming algorithm, and equalization algorithm.

• Journal of Mechanical Science and Technology
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• v.18 no.8
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• pp.1461-1469
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• 2004

Acoustic characteristics in an industrial gas-turbine combustor are numerically investigated by a linear acoustic analysis. Spatially non-homogeneous temperature field in the combustor is considered in the numerical calculation and the characteristics are analyzed in view of acoustic instability. Acoustic analyses are conducted in the combustors without and with acoustic resonator, which is one of the acoustic-damping devices or combustion stabilization devices. It has been reported that severe pressure fluctuation frequently occurs in the adopted combustor, and the measured signal of pressure oscillation is compared with the acoustic-pressure response from the numerical calculation. The numerical results are in good agreement with the measurement data. In this regard. the phenomenon of pressure fluctuation in the combustor could be caused by acoustic instability. From the numerical results for the combustor with present acoustic resonators installed, the acoustic effects of the resonators are analyzed in the viewpoints of both the frequency tuning and the damping capacity. It is found that the resonators with present specifications are not optimized and thus, the improved specification or design is required.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.2
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• pp.258-266
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• 2012

Recently, Acoustic Emission (AE) technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the rolling element bearing problems and Wavelet transform is a powerful method to detect faults occurred on gearboxes. However, exact method for AE signal is not developed yet. Therefore, in this paper, two methods, which is Hilbert transforms (HT) and Hilbert-Huang transforms (HHT), will be compared for development a signal processing method for early fault detection system by using AE. AE signals were measured through a fatigue test. HHT has better advantages than HT because HHT can show the time-frequency domain result. But, HHT needs long time to process a signal, which has a lot of data, and has a disadvantage in de-noising filter.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.26-32
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• 2007

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.342-348
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• 2005

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.18-24
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• 1999

ThisPaper investigates the feasibility of using acoustic emission signal analysis for the detection of built-up edge during machining. Experiments were conducted on a CNC-lathe using conventional carbide insert tools under various cutting conditions. The cutting forces were also measured for comparisons. Experimental evidence is presented which indicates that the presence of a built-up edge can significantly affect the generation of acoustic emission in metal cutting. It is shown that under conditions in which a built-up edge is generated, the variation of $AE_{rms}$ signal with cutting speed can be quite different from the generally accepted linear, monotonic increase as previously reported. The feasibility of utilizing $AE_{rms}$ in built-up edge sensing is suggested.