• 한국기계가공학회지
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• 제2권3호
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• pp.34-40
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• 2003

This paper describes evaluation and monitoring methods of machining characteristics for developed micro grooving machine. Experiments were conducted under various process conditions such as spindle revolution speed, feed rates and depth of groove V and U shape of blade and STD11 were used in this experiment. The status of grooving was evaluated through analysis of the Acoustic emission (AE) signal resulted in each process condition. Based on the analysis, this paper examined the possibility of monitoring adapting fuzzy logic. In conclusion, this paper presented the possibility of monitoring in process adapting AE technology and appropriate micro grooving condition.

• 한국생산제조학회지
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• 제8권6호
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• pp.71-77
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• 1999

Monitoring of Cutting tool wear is a critical issue in automated machining system and has been extensively studied for many years. An austempered ductile iron(ADI) exhibits the excellent mechanical properties and the wear resistance. ADI has generally the poor machinability due to the characteristic. This paper presents the in-process detection of flank wear of cutting tools using the acoustic emission sensor and the digital oscilloscope. The amplitude level of AE signal(AErms) is mainly affected by cutting speed and it is proportional to cutting speed. There have been the relationship of direct proportion between the amplitude level of AE signals and the flank wear width of cutting tool. The flank wear with corresponding to the tool life is successfully detected with the monitor-ing system used in this study.

• 한국정밀공학회지
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• 제16권5호통권98호
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• pp.186-193
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• 1999

Sensor feedback for process control is one of the essential elements is an automated deburring procedure. This paper presents the implementation of acoustic emission (AE), which has been developed as a feedback sensing technique for precision (mechanical) deburring, in a precision laser deburring process. AE signals were sampled for laser machining/deburring under various experimental conditions and analyzed using several signal-processing methods including AErms and spectral analysis. The results, such as the sensitivity of AE signals for different laser cutting depths, edge detection capability and the frequency analysis show a clear correlation between physical process parameters and the AE signals. A subsequent control strategy for deburring automation is also briefly discussed.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 추계 학술발표회 논문집
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• pp.249-252
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• 2006

When concrete is subjected to uniaxial compression, the failure process is normally initialed from a localized zone. The localization of failure governs structural behaviors of concrete. In this paper, the compressive strength and failure behavior of recycled coarse aggregate concrete with different replacement level of recycled coarse aggregates are investigated using acoustic emission(AE). AE characteristics of concrete were investigated during the entire loading period. For these purpose, four recycled coarse aggregate replacement level (i.e 0%, 30%, 60% and 100%) were considered in this paper. Result from this study show AE signal, AE method can apply to investigate a compressive failure mode according to recycled coarse replacement level.

• 한국항공운항학회지
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• 제17권4호
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• pp.42-47
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• 2009

Recently, the wide range of the composite materials is used for the making airplanes, trains and automobiles body for the lightweight. Despite having complex structures, composite materials usually have well defined mechanical characteristics. However, composite materials are difficult to understand the fracture mechanism clearly by simple mechanical test. Nondestructive evaluation (NDE) combined with mechanical testing can play a more important role and especially Acoustic Emission Testing (AET) would become known to be a useful tool to assess damage and fracture behavior of composites. In this study The experiment was performed to acquire the acoustic emission signal during tensile test using unidirectional CFRP specimen and the data was analyzed the acoustic emission parameters with the waveform.

• 비파괴검사학회지
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• 제10권1호
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• pp.84-90
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• 1990

By discriminating the wave propagation paths in cylindrical vessels, a technique for AE source location has been proposed. This method is based on the path difference between several propagating directions from a source to a sensor. One sensor can receive multiple waveforms sequentially including a direct arrival and several others propagated through the circumferential direction. An wave front normally propagates in all directions and as many waveforms can reach the sensor until the signal faded out by attenuation. Only the first four arrivals suffice the condition for calculating the source location. The proposed method was examined for an actual cylindrical vessel by the source location experiment using simulated AE sources. The test showed very promising results and the method can be utilized for a simple AE source location without multi-channel instruments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 C
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• pp.1652-1654
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• 2002

The defects making partial discharge(PD) in a C-GIS(Cubicle Insulated Switchgear) initiate acoustic wave which can be detected using acoustic emission sensor placed outside or inside the C-GIS enclosure. In this paper, partial discharge property for 2 locations for AE sensor and 3 locations for defects in C-GIS are presented and PD waveforms were analyzed by PRPDA(Partial Resolved Partial Discharge Analysis). As a result, using post amplifier having gain of 10,000 and band pass filter having $20kHz{\sim}300kHz$, resolution of waveforms AE sensor signal by detected was good. Noise level was about 80 mV.

• 비파괴검사학회지
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• 제15권4호
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• pp.520-530
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• 1996

본 연구에서는 음향방출법을 이용하여 로터리 압축기의 인공 결함을 분류하기 위한 연구를 수행하였다. 이를 위해 프로그램을 개발하였고 선형 분류기, 경험적 Bayesian 분류기, 신경 회로망 분류기를 함께 사용하여 비교하였다. 그 결과 신경 회로망 분류기가 인식률 면에서 유리하였으며 신경 회로망 분류기의 경우 99%이상의 인식률을 얻을 수 있었다.

• 한국정밀공학회지
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• 제17권4호
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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.

• 한국기계가공학회지
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• 제8권1호
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• pp.31-36
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• 2009

Micro-machining technology has been adopted for shape accuracy of micrometer and sub-micrometer scale, surface roughness of tens nanometer in industries. In micro-machining process the quality of machined surface is derived from machining condition and tooling. This paper investigates AE(acoustic emission) and cutting force signals according to machined surface quality related to machining condition. Machined surface quality was analyzed by the AE and cutting force parameter which reflect surface morphology. The characteristics of signal were extracted for process optimization by monitoring both the tool condition and the machined surface texture in micro end milling process.