• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1995년도 추계학술대회 논문집
• /
• pp.101-104
• /
• 1995

A acoustic emission (AE) sensor has been used to monitor tool were during milling process. The relation between tool wear and AE RMS (Root mean Square) signal was investigated experimentally. A avaliable monitoring index for monitoring toolwear was newly extracted form AE RMS. And on-line monitoring program was developed. The proposed monitoring system has verified experimentally by roughing end milling titanium alloy with TIN coated HSS tool.

• 대한기계학회논문집
• /
• 제10권6호
• /
• pp.906-915
• /
• 1986

본 논문에서는 에너지 법칙(energy principle)에 기초한 AE RMS값과 절삭 파 라미터들 사이의 해석적인 관계를 구하기 위하여 Lee와 Shaffer의 미끄름선장 영역을 변형되는 부피로 가정하여 이론적인 식을 제시하였으며 Al의 2차원 절삭시험을 통하여 이 관계가 절삭과정의 감시에 유용하리라는 것을 확인하였다.

• 한국정밀공학회지
• /
• 제15권6호
• /
• pp.48-57
• /
• 1998

Abrasive waterjet(AWJ)은 가공시 열에 의한 가공경화가 없기 때문에 유리, 세라믹, 타이타늄및 금속복합재료와 같은 난삭재의 가공기술로 사용이 증가되었다. Acoustic emission(AE)신호에 의한 AWJ 세라믹 drilling가공시 On-Line Monitoring의 가능성이 고찰되었다. 기계 적인 물성이 서로 상이한 3종류의 세라믹이 본 연구에서 사용되었으며, AE신호는 AWJ drilling의 깊이를 monitoring하는데 유용함을 알 수 있었고 또한 세라믹의 material removal mechanisms을 규명하였다.

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

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 추계학술대회 논문집
• /
• pp.56-60
• /
• 1996

An experimental study on the grinding temperature and Acoustic Emission(AE) signals due to the different shapes of wheel was conducted. The grinding characteristics by slotted shapes of wheel changed by width and helical angle, were compared with those by general one. Lower grinding temperature was obtained for 30$^{\circ}$ helical angle with 10mm width, Root Mean Square(RMS) values of AE signals were higher for slotted wheel rather than general one.

• 비파괴검사학회지
• /
• 제11권1호
• /
• pp.31-37
• /
• 1991

Acoustic emission(AE) signals detected during metal cutting were applied as the experimental test to sensing tool wear and chipping on the NC vertical milling machine. The in-process detection of cutting tool wear including chipping, cracking and fracture has been investigated by means of AE in spite of vibration or noise through intermittent metal cutting, then the following results were obtained 1) When the tool wear is increased suddenly, or the amplitude of AE signals changes largely, it indicates chipping or breaking of the insert tip. 2) It was confirmed that AE signal is highly sensitive to the cutting speed and tool wear. 3) At the early period of cutting, the wear were large and RMS value increased highly by the influence of minute chipping and cracking, etc. Therefore, the above situations should be considered for the time when the tool would be changed.

• 한국정밀공학회지
• /
• 제20권11호
• /
• pp.47-54
• /
• 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.

• 한국정밀공학회지
• /
• 제11권4호
• /
• pp.69-76
• /
• 1994

AE(Acoustic Emission) signal is correlated to workpiece material, cutting conditions and tool geometry during metal cutting. The relationship between AE signal and cutting parameters can be obtained by theoretical model and experiments. The value of CR(Count Rate) is nearly constant in stable cutting, but when the chatter vibration occours, the value of CR is rapidly increased due to the vibration deformation zone. By experimental signal processing of AE, it is more effective than by RMS(Root Mean Square) measurement to detect the threshold of chatter vibration by CR measurement.

• 동력기계공학회지
• /
• 제11권1호
• /
• pp.45-50
• /
• 2007

Acoustic emission technology is applied to diagnosis the internal leak and operating conditions of the major valves at nuclear power plants. The purpose of this study is to verify availability of the acoustic emission as in-situ diagnosis method. In this study, acoustic emission tests are performed when the pressurized high temperature steam flowed through gate valve(1st stage reheater valve) and glove valve(main steam dump valve) on the normal size of 4 and 8". The valve internal leak diagnosis system for practical field was designed. The acoustic emission method was applied to the valves at the site, and the background noise was measured for the abnormal plant condition. To improve the reliability, a judgment of leak on the system was used various factors which are AE parameters, trend analysis, signal level analysis and RMS(root mean square) analysis of acoustic signal emitted from the valve operating condition internal leak.

• 한국생산제조학회지
• /
• 제23권4호
• /
• pp.330-336
• /
• 2014

The continuous chip generated in cutting process deteriorates workpiece, tool, and machine tool system. It is necessary to treat this continuous chip in ductile material machining condition for stable cutting. This paper deals with the chip control method using acoustic emission(AE) signal in pure copper turning operation. AE raw signals, root mean square(RMS) signals and wavelet transformed signals measured in turning process are introduced to analysis for chip patterns. With analysis of AE signals, it is obtained that the produced chip patterns are correlated with the specified AE signals which are transformed by fuzzy pattern algorithm. By this experimental investigation, the chip patterns can be classified at significant level in pure copper machining process and controlled from continuous chips to reduced-length stable chips.