• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1243-1249
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• 2008

Gear system has been widely used in industrial applications and unexpected failures of gears are not only extremely damaging but also leading to economic losses. So, early detection of fault is important for diagnosis machine condition. And acoustic emission is an efficient non-destructive testing technique fur the diagnosis of machine health and is useful technique far early detection of fault because it can find low-amplitude and high-frequency signal on account of high sensibility. Therefore, in this paper, the AE signal was measured and preprocessed using envelope analysis for gearbox with misalignment between pinion and gear. And then the gear misalignment's vibration characteristic were analyzed.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.674-679
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• 1994

Acoustic signal such as speech and scattered sound, are generally a nonstationary process whose frequency contents vary at any instant of time. For time-varying signal, whether a nonstationary or a deterministic transient signal, a traditional frequency domain representation does not reveal the contents of signal characteristics and may lead to erroneous results such as the loss of desired characteristics features or the mis-interpretation for a wrong conclusion. A time-frequency domain representation is needed to characterize such signatures. Pseudo Wigner-Ville distribution (PWVD) is ideally suited for portraying nonstationary signal time-frequency domain and carried out by adapting the fast Fourier transform algorithm. In this paper, the important properties of PWVD were investigated using both stationary and nonstationry signatures by numerical examples PWVD was applied to acoustic sigtnatures to demonstrate its application for time-ferquency domain analysis.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.139-142
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• 2004

The object of the present work is the acoustic emission energy analysis of subambient pressure tri-pad slider. Head/disk interaction during start/stop and constant speed were detected by using acoustic emission (AE) test system The frequency spectrum analysis is performed using the AE signal obtained during the head/disk interaction Natural frequency analysis was performed using Ansys program. Acoustic emission energy was calculated for the slider modes.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.6
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• pp.440-446
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• 2015

Acoustic signal is emitted from a vessel and received by a cylindrical array sensor at some distance from the vessel. Acoustic signal is the source for a cylindrical array sensor which is designed to detect the acoustic signal. Cylindrical array sensors seldom have an ideal hydrodynamic shape and are not sufficiently robust to survive without some protection and they are normally housed in a sonar dome. Reflected signals by some structure inside a sonar dome make unwanted signals. Therefore, an acoustic baffle is used to minimize unwanted signals. The performance of the acoustic baffles can be determined from the acoustic numerical analysis at the design stage. In this study, finite element method was used to analyze the acoustic field around the cylindrical array sensor and baffle effects. The baffle performance can be defined the echo reduction. To show the baffle performance, the specimens were made for pulse tube test and echo reductions were measured during the test. In this paper, the effect of echo reduction of the acoustic baffle was discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.9
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• pp.979-986
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• 2015

Security solutions using fiber-optic cable have not yet secured a solid technical stability, through which the Acoustic detection security system also did not have a complete defense techniques such as false alarm and detecting fail due to a number of variables. In this paper, we investigate 4 characteristics for the channel of underwater acoustic communication. We also construct detection system as a construction method for security system using optical cable through the analysis of acoustic signal in underwater. We perform analysis of signal characteristics and noise of underwater optical cable, and then we confirms the possibility of real application.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.938-942
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• 2008

To detect the failures in machine, the signals of current, vibration and acoustic emission are widely used in industry. And unexpected failures of gears are not only extremely damaging but also lead to economic losses. In this paper, to detect the misalignment occurred at between two gears in gearboxes, the signals of current, vibration and AE were measured at gearbox and motor power line. FFT(Fast Fourier Transform) was used for current and vibration signal analysis to find gear failure frequency. Especially, the envelop analysis and wavelet transform were applied for AE signal. Therefore, compared with the results of three kinds of signal, the possibility of earily detection by AE is identified or checked.

• Speech Sciences
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• v.5 no.1
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• pp.151-165
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• 1999

This paper describes a series of researches to diagnose vocal diseases using the statistical method and the acoustic signal analysis method. Speech materials are collected at the hospital. Using the pathological database, the basic parameters for the diagnosis are obtained. Based on the statistical characteristics of the parameters, valid parameters are chosen and those are used to diagnose the pathological speech signal. Cepstrum is used to extract parameters which represents characteristics of pathological speech. 3 layered neural network is used to train and classify pathological speech into normal, benign and malignant case.

• Journal of the Korean Society for Railway
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• v.4 no.3
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• pp.79-86
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• 2001

The signal pattern recognition method by acoustic emission signal is applied to detect and classify the defects of a journal bearing in a power plant. AE signals of main defects such as overheating, wear and corrosion are obtained from a small scale model. To detect and classify the defects, AE signal pattern recognition program is developed. As the classification methods, the wavelet transformation analysis, the frequency domain analysis and time domain analysis are used. Among three analyses, the wavelet transformation analysis is most effective to detect and classify the defects of the journal bearing..

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.905-910
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• 2008

Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

• The KSFM Journal of Fluid Machinery
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• v.5 no.1 s.14
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• pp.13-19
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• 2002

In the present study, a numerical simulation is performed for the flow through a cooling fan. The computation was performed by using commercial code, STAR-CD. A rotating fan was simulated by rotational motions using MRF (Multiple Rotating Reference Frame) in a steady-state analysis and sliding interface (rotating meshes) in an unsteady-state analysis. The results of numerical computation were in good agreement with experimental data. In order to calculate the acoustic signal, the unsteady flow-field was firstly calculated. The acoustics of the fan is calculated by using acoustic analogy based on the unsteady flow-field. The predicted acoustic signal shows the characteristics of the uneven bladed-fan.