• KSTLE International Journal
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• v.1 no.1
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• pp.29-33
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• 2000

In this study, a methodology is developed and confirmed to find the physical contact between the slider and disc due to the defects of disk during head seeking operation using acoustic emission (AE) signal. The head/disk contact was detected during random and standard seeks, whereas no contact was detected during track fellowing. During standard and random seeks, the torsion mode of slider excitation was observed at 680KHz. Therefore, it is thought that AE technique can be used as an alternative method of the glide test by monitoring existence of the torsional mode of the slider during seek operation or can be used to detect the spacing loss during seeking operation. By appropriately choosing the location of the sensor an order of magnitude increase in the sensitivity for RMS AE signal is observed. Therefore we can find take-off velocity clearly with high signal to noise ratio of AE signal.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.304-309
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• 2011

A monitoring system for magnetic abrasive polishing process is necessary to ensure the polishing products the high quality and integrity. Acoustic emission (AE) signal is known to reflect the material removal phenomena in other machining processes. In a case of the magnetic abrasive polishing of non-magnetic materials, application of AE method is very difficult because of lower machining force on the surface of workpiece and the level of AE signal is extremely lower. In this study, AE sensor-based monitoring system is applied to the magnetic abrasive polishing. The relation between the level of the AE RMS and the surface roughness during the magnetic abrasive polishing of magnesium alloy steel is investigated.

• Bulletin of the Korean Chemical Society
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• v.20 no.9
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• pp.1040-1044
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• 1999

A micro porous PTFE membrane desolvator (MMD) was built and evaluated for the on-line removal of organic solvents to facilitate the determination of trace metal contaminants in the solvents by ICP-AES. Three organic solvents, isopropyl alcohol (IPA), methanol, and dimethy sulfoxide (DMSO) were studied. The MMD reduced organic solvent concentration in the sample aerosol stream by 82% to 89%, as indicated by monitoring C(I) emission. Net signal intensity of Fe, Al, and Cu was increasing with higher organic solvent concentration, with the rate of increase being solvent dependent. The signal intensities for Mg and Pb followed the trend with the C(I) signal. Changing the sweep gas flow rate affected the optimum signal intensity. Wine samples were analyzed by the method of standard addition. The concentrations of B, Al, and Mg were determined with a relative precision of less than 2.3%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.58-63
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• 1993

The charactistics of AE(Acoustic Emission) signal is related to cutting conditions, tool materials and tool geometry in metal cutting. The tool geometry change which is derived from tool wear affects the source of AE signal in machining process. The relationship between AE signal and tool wear was experimentally investigated. THe value of RMS(Root Mean Sequare) and Amplitude of AE signal were increased in tool wear condition. Also the high value of Count per Hit and Count vs. Frequency was observed in this condtion. As a result, tool wear can be effectively detected by AE signal during cutting operation.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.32-32
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• 2011

Plasma etching is used in microelectronic processing for patterning of micro- and nano-scale devices. Commonly, optical emission spectroscopy (OES) is widely used for real-time endpoint detection for plasma etching. However, if the viewport for optical-emission monitoring becomes blurred by polymer film due to prolonged use of the etching system, optical-emission monitoring becomes impossible. In addition, when the exposed area ratio on the wafer is small, changes in the optical emission are so slight that it is almost impossible to detect the endpoint of etching. For this reason, as a simple method of detecting variations in plasma without contamination of the reaction chamber at low cost, a method of measuring plasma impedance is being examined. The object in this research is to investigate the suitability of using plasma impedance monitoring (PIM) with statistical approach for real-time endpoint detection of $SiO_2$ etching. The endpoint was determined by impedance signal variation from I-V monitor (VI probe). However, the signal variation at the endpoint is too weak to determine endpoint when $SiO_2$ film on Si wafer is etched by fluorocarbon plasma on inductive coupled plasma (ICP) etcher. Therefore, modified principal component analysis (mPCA) is applied to them for increasing sensitivity. For verifying this method, detected endpoint from impedance analysis is compared with optical emission spectroscopy (OES). From impedance data, we tried to analyze physical properties of plasma, and real-time endpoint detection can be achieved.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.23-30
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• 2001

In this paper, the discharge image of NO particles wire-cylinder type electrode in the discharge reactor where AC dielectric barrier type corona discharge occurred and horizontal and vertical signal intensity at each flourescence emission during discharge and the horizontal and vertical signal strength of NO particles at flourescence emission wavelength band[236[nm], 247[nm]], were measured were measured by ICCD Camera. In addition discharge images and signal intensities in accordance with discharge time were measured to figure out the discharge mechanism. It was found that the strongest horizontal and vertical signal intensity of NO particles were observed at 247[nm] band, but no big difference in the horizontal and vertical signal intensity in accordance with discharge time was seen. In particular, the phenomenon image occuring inside the discharge reactor and wavelength ware able to be carried based on the measured data.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.191-192
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• 2002

The scuffing failure is a critical problem in modern machine components, especially for the requirement of high efficiency and small size. In this study. scuffing experiments are conducted using Acoustic Emission(AE) measurement by an indirect sensing approach to detect scuffing failure. Using AE signals we con get and indication about the state of the friction processes, about the quality of solid and liquid layers on the contacting surface in real time. The FFT(Fast Fourier Transform)analyses of the AE signal are used to understand the interfacial interaction and the relationship between the AE signal and the state of contact is presented.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.240-246
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• 2000

An in-process estimation of the ground surface roughness is a bottle-neck and an essential field in conventional grinding operation. We defined the dimensionless average roughness factor (D.A.R.F) that exhibits a roughness characteristics of ground surface. The D.A.R.F was composed easily of the absolute average and the standard deviation values which were the analytic parameters of the acoustic emission (AE) signal generated during the machining process. The theoretical equation between the surface roughness and the D.A.R.F has been derived from the linear regressive analysis and verified its availability through the experimentation on the surface grinding machine.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• KSTLE International Journal
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• v.6 no.1
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• pp.17-20
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• 2005

The object of the present work is the natural lre%uency analysis of femto slider, HeaHdisk interaction during starustop and constant speed were detected by using the acoustic emission (AE) test system. The frequency spectrum analysis wasperformed using the AE signal obtained during the head/disk interaction. The FFT (Fast Fourier Transform) analysis of the AEsignals is used to understand the interaction between the AE signal and the state of contact. Natural frequency analysis wasperformed using the ANSYS program. The results indicate acceptable accordance of finite element calculation results with theexperimental results.