• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.987-990
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• 2000

In modern manufacturing industry such as aerospace, vehicle and die/mold industry, the high hardness malarial which is remarkable in aspects of durability is effectively used. The high-speed and precision machining technology has been applied in these fields. In this study, efficient sensors in high-speed machining by observing similar tendency through comparing cutting force with AE signal, gap sensor signal and accelerometer signal are selected, and machinability of high-speed machining is experimentally evaluated. We performed a basic research for sensing system construction to monitor a machine tool and machining condition.

• 대한기계학회논문집A
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• 제28권6호
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• pp.867-875
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• 2004

In order to inspect burr geometry and hole quality in micro-drilling processes, a cost-effective method using an image processing and shape from focus (SFF) methods on the machine tool is proposed. A CCD camera with a zoom lens and a novel illumination unit is used in this paper. Since the on-machine vision unit is incorporated with the CNC function of the machine tool, direct measurement and condition monitoring of micro-drilling processes are conducted between drilling processes on the machine tool. Stainless steel and hardened tool steel are used as specimens, as well as twist drills made of carbide are used in experiments. Validity of the developed system is confirmed through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1570-1575
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• 1991

The feasibility of using an adaptive resonance network (ART2) with unsupervised learning capability for too] wear detection in turning operations is investigated. Specifically, acoustic emission (AE) and cutting force signals were measured during machining, the multichannel AR coefficients of the two signals were calculated and then presented to the network to make a decision on tool wear. If the presented features are significantly different from previously learned patterns associated with a fresh tool, the network will recognize the difference and form a new category m worn tool. The experimental results show that tool wear can be effectively detected with or without minimum prior training using the self-organization property of the ART2 network.

• 한국생산제조학회지
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• 제5권3호
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• pp.15-21
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• 1996

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE(Acoustic Emission) signals, while cutting stainless steel by end mill on the machining center. The results of this study were that RMSAE tends to increase linearly along with the increase of the cutting speed, and it was more sensitive to depth of cut than to the variation of feed rate at the same cutting conditions, and RMSAE increases around 0.21mm flank wear hereby AE-HIT also increases. AE signals depend upon tool wear and fracture from the above results. Therefore, the AE signals can be utilized in order to monitor the tool condition.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1207-1213
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• 2006

This paper shows that case-based reasoning (CBR), an artificial intelligence technique, is a quite efficient tool in monitoring financial market against its possible collapse. For this purpose, daily financial condition indicator (DFCI) monitoring financial market is built on CBR and its performance is compared to DFCI on neural network. This study is empirically done for the Korean financial market.

• 한국공작기계학회논문집
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• 제17권1호
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• pp.98-105
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• 2008

In this paper, the system for monitoring process of aluminum laser welding was developed using the light signal emitted from the plasma which comes from interaction between material and laser. Photodiode for monitoring system was selected based on the spectrum analysis of light from plasma and keyhole. Behavior of plasma and keyhole was analyzed through the sensor signals. Value of sensor signal represented the light intensity and fluctuation of signal indicated the stability of plasma and keyhole. For the relation between welding condition and sensor signals, the input power and weld geometry greatly effected on the average of each sensor signals. Using the feature values of signals, estimation model for tensile strength of weld was formulated with neural network algorithm. Performance of this model was verified through coefficient of determination and average error rate.

• 한국정밀공학회지
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• 제12권3호
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• pp.5-14
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• 1995

In recent years, the automization of cutting machine tools has been developed very fast. Hance, the in-process detection of cutting condition is very important for automatic manufacturing system in factory. Acoustic Emission(AE) has been widely used in monitoring the cutting conditions, because of high sensitivity of AE signal and low cost of AE equipment. This experimental study deals with the relations between AE signal, cutting force charcteristics and tool wear in the machining of SUS304. Face milling operation is used for the analysis between tool wear and AE signal.

• 한국정밀공학회지
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• 제21권5호
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• pp.99-105
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• 2004

Internet provides the useful method to monitor the current states of the machine tool no matter where a personnel monitors it. In this paper, a monitoring method of the torque of the machine tool's spindle induction motor using interne is suggested. To estimate the torque accurately, spindle driving system of an CNC lathe is divide into two parts, induction motor part and mechanical part attached to the induction motor spindle. Magnetizing current is calculated from the measured 3 phase currents without speed sensor used to estimate the torque generated by an induction motor. In mechanical part of the system, some of the torque is used to overcome friction and remaining torque is used to overcome cutting force. An equation to estimate friction torque is drawn as a function of cutting torque and rotation speed. Graphical programming is used to implement the suggested algorithm. to monitor the torque of an induction motor in real time and to make the estimated torque monitored on client computers. Torque of the spindle induction motor is well monitored on the client computers in about 3% error range under various cutting conditions.

• 한국통신학회논문지
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• 제30권10B호
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• pp.630-638
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• 2005

네트워크 및 종단 노드의 시스템에 걸친 제한된 자원을 활용하여 실현되는 영상/음성 전달 서비스를 위한 멀티미디어 응용 프로그램의 품질을 보장하기 위해서는 지연, 지터, 손실과 같은 전송 상태와 CPU, 메모리의 사용량과 같은 시스템의 상태를 동시에 관찰하는 것이 필요하다. 본 논문에서는 액세스그리드 (Access Grid) 경우와 같이 IP 멀티캐스트 상에 동작하는 RTP/RTCP에 기반한 실시간 미디어 응용 프로그램을 대상으로 동적/정적 모니터링 방식을 혼용하여 멀티캐스트 상태와 시스템 상태를 측정하는 혼성 모니터링 방식을 제안한다. 또한 종단간 전송 품질이 저하된 경우 제안한 모니터링 방식에서 측정된 결과를 비교/분석하여 품질 저하의 원인을 판단하고 원인에 적합한 대응방안을 연계하고i라 한다. 이 결과를 바탕으로 네트워크/시스템의 상태 변화에 적응적인 영상/음성 전송 서비스의 가능성을 타진하고 종단간 전송 품질 저하 방지를 위한 효과를 예상한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.513-517
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• 2005

The condition monitoring of rotating machinery such as turbines, pumps and compressors, determine what repairs are needed to avoid shutdown and disassembly of the machine in an industrial plant Many diagnosis methods have been developed for use when the machine is running at steady state, the stationary condition. But much information can be gained about a rotor's condition during non-stationary conditions such as run-up and run-down. Order tracking analysis is a powerful tool for analyzing the condition of a rotating machine when its speed changes over time. Powerful OTA using digital signal processing has some advantages(cheap hardware, the powerful methods, the accurate post processing) and also some disadvantages(calculation time, high speed sampling). New OTA tool based on the chirplet transform is similar to the short time Fourier transform. But, it has good resolution at high speed like other OTA methods based STFT and more resolution for constant frequency components than re-sampling OTA.