• 한국정밀공학회지
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• 제13권4호
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• pp.136-142
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• 1996

Automatic monitoring of cutting process is one of the most important technology in machining. AE sensing technology has been applied to monitoring process and proved to be effective in detecting tool abnor- malities such as tool wear and fracture. In this experimental study. AE signals were detected from the tool holder for continuous and interrupted cutting, which obtained from changing workpice material configuration, under control of constant cutting speed from CNC lathe. From statistical and frequency analysis, the AE signals were analyzed to obtaining the characteristics of continuous and interrupted cutting conditions and tool failure. The Kurtosis values decreased but RMS voltages increased as the cutting speed increased, in both continuous and interrupted cutting. RMS voltage is suddenly increased but Kurtosis value is suddenly decreased when tool failure condition. Power spectrum density of AE signals when tool failure reaches extreme value around 0.065 cycles/ .mu. m.

• 한국기계연구소 소보
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• 통권19호
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• pp.61-68
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• 1989

As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.

• 대한기계학회논문집
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• 제17권8호
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• pp.1910-1920
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• 1993

An experimental study to investigate the unconventional chip formation called triangulation of chip in cutting with a SPRT (self-propelled rotary tool) is performed using acoustic emission (AE) signal analysis. In doing that, a quantitative model of the AE RMS signal in triangulation with a SPRT is first developed. The predicted results from this model show good correlation between the AE RMS signal and the general characteristics of triangular chip formation. Then, effects of various process parameters such as cutting conditions (cutting speed, depth of cut, oblique angle and normal rake angle) and the work material properties on the chip formation in cutting with a SPRT are explored. Special attention is paid to the work material properties which are found to have significant effects on triangulation.

• 비파괴검사학회지
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• 제14권2호
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• pp.122-131
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• 1994

일반적으로 회전기기의 저어널 베어링 부분은 윤활유 공급의 부족이나 윤활층에 이물질이 혼입되면 시스템의 고장이나 가동중단 등의 원인이 되기도 한다. 따라서 베어링 손상에 기인하는 사고와 관련된 안전운전 문제와 유지비용의 절감을 위해 여러가지 파괴 및 비파괴시험법들이 사용되어 왔다. 본 연구에서는 저어널 베어링에서 가장 발생하기 쉬운 윤활층에의 이물질 혼입에 의해 야기되는 베어링 파손의 조기검출을 위해 음향방출 기술을 적용하였으며, 전보의 연구에 이어 좀더 정량적이고 체계적인 실험을 수행하였다. 실험실용으로 직접 제작한 모의 베어링 시스템을 이용하여 여러 형태의 인위적인 이물질 혼입 상태를 만들어 실험하였으며 베어링 손상 및 결함 형태의 해석을 위해 AE rms level, 파형분석, AE 변수 등의 여러 파라메터를 사용하여 분석 고찰하였다. 그 결과 AE rms level의 변화가 이물질 혼입의 영향에 민감함을 보여주었으며 AE 변수 등 다른 정보들로부터 손상 원인별로 신호형태를 확인할 수 있었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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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.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.39-45
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• 2000

This paper describes the fundamental investigations on the in-process monitoring techniques focused on Acoustic Emission(AE) based on analytical method. Experiments were conducted on a CNC lathe using conventional carbide insert tools under various cutting conditions. As the result of this study a suggestion is given about the multi-purpose use of AE-signals detected with a single sensor for the monitoring of tool wear, built-up edge and chatter vibration in turning process.

• 대한기계학회논문집A
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• 제24권12호
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• pp.2891-2898
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• 2000

The objective of this paper is to develop a fiber-optic acoustic emission(AE) sensor applicable to on-line monitoring systems which is suitable for long-distance signal transmission. An AE sensor was developed by use of a fiber-optic cantilever and an extrinsic Fabry-Perot interferometer(EEPI). The efficiency of signal processing was improved by driving the high frequency AE signals into the low frequency ones. In order to verify the developed sensor, the tensile and the pencil lead fracture(PLF) tests were performed including the experiment showing the Kaiser effect. Form tests, AE signals were successfully detected in the elastic-plastic deformation range, especially higher signals at the crack propagation. The developed sensor was expected to be used for an on-line monitoring of crack propagation in mechanical system.

• 한국정밀공학회지
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• 제2권1호
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• pp.62-71
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• 1985

This is a study on the monitoring technique in tool failure and tool life by AE method. The relation between amplitude level of AE signal and flank wear width was studied by experiments. The relation between amplitude level of AE signal and tool life was also studied. As the result, it was observed that amplitude level of AE signal was only affected by cutting velocity. Amplitude level of AE signal was directly proportional to flank wear width and the increasing rate was related to cutting velocity. So, the relation between amplitude level of AE signal and tool life was represented as follow: $CT^n$ = $AE_{rms}$ where, n=0.35 C=9.5*$10^{-2}$

• 한국정밀공학회지
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• 제22권10호
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• pp.90-98
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• 2005

A monitoring system is necessary to make the polishing process more reliable in order to ensure the high quality and performance of the final products. Generally, AE (Acoustic Emission) is known to be closely related to the material removal rate (MRR). As the surface becomes rougher, the MRR and AE increase. Therefore, the surface roughness can be indirectly estimated using the AE signal measured during the polishing. In this study, an AE sensor-based monitoring system was fabricated to detect the very small AE signal resulting from the friction between a tool and a workpiece during polishing. The performance of this monitoring system was estimated according to polishing conditions, the relation between the level of the AE RMS and the surface roughness during the polishing was investigated.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1998년도 춘계학술대회 논문집
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• pp.172-177
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• 1998

An experimental study on the prediction of grinding wheel wear by dual detection methods was conducted by the laser displacement and acoustic emission(AE) system. The laser displacement sensor was located above the head of the grinding wheel and the AE sensor was set under the workpiece, where the wheel were condition can be detected. It was found that the dual detection methods by laser displacement system and AE system made it possible to predict the wheel wear. From the experiments, the root mean square(RMS) values both methods was found to be proportional to the grinding wheel wear.