• 한국정밀공학회지
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• 제12권5호
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• pp.25-32
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• 1995

In highly automated milling process, in-process monitoring of the malfunction is indispensable to ensure efficient cutting operation. Among many malfunctions in milling process, chatter vibration deteriorates surface finish, tool life and productivity. In this study, the monitoring system of chatter vibration for face milling process is proposed and experimentally estimated. The monitoring system employs two types of sensor such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are extracted in time domain for the input patterns of neural network to reduce time delay in signal processing state. The resultes of experimental evaluation show that the system works well over a wide range of cutting conditions.

• 한국정밀공학회지
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• 제12권12호
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• pp.120-129
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• 1995

This study introduces a tool wear monitoring technology in face milling operation comprised of an unsupervised neural network. The monitoring system employs two types of sensor signal such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are calculated for te input patterns of neural network. ART2 neural network, which is capable of self organizing without supervised learning, is used for clustering of tool wear states. The experimental results show that tool wear can be effectively detected under various cutting conditions without prior knowledge of cutting processes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.69-73
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• 1996

Tool wear monitoring is very important aspect in metal cutting because tool wear effects quarity and precision of workpiece, tool life etc. In this study we detected force signal through tool dynamometer in turning and using it we conducted 6th AR modeling and fractal analysis. Finally the back-propagation model of the neural network is utilized to monitor tool wear and features are extracted through AR model and fractal analysis.

• 한국기계가공학회지
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• 제2권3호
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• pp.13-19
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• 2003

The high speed machining technology has been improved remarkably in die/mold industry with the growth of parts and materials industries. Though the spindle speed of machine tool increases, the condition monitoring techniques of the machine tool, tool and workpiece in high speed machining ate incomplete. In tins study, efficient sensing technology in high speed machining is suggested by observing the characteristics of cutting force, gap sensor and accelerometer signal also, machinability of high-speed machining is experimentally evaluated sensing technique to monitor the machine tool and machining conditions was performed.

• 한국생산제조학회지
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• 제25권6호
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• pp.401-409
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• 2016

The formation of micro-burrs in micro-milling processes causes several problems related to productivity and surface integrity. It should be minimized and suppressed by effective monitoring of the cutting conditions. This paper presents the correlation between the micro-burr length and cutting signals in the micro-milling process of an Al alloy (Al6061-T6). The acoustic emission (AE) signals and cutting force signals are acquired during the experiments. The characteristics of the cutting signals are obtained by analyzing the AE root mean square value and resultant cutting force. In addition, the micro-burr length is measured according to the cutting conditions by analyzing a scanning electron microscopy image of the machined surface. The results of this study can be used to enhance the surface quality of micro parts.

• 대한기계학회논문집
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• 제16권4호
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• pp.707-722
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• 1992

본 연구에서는 공구의 큰 파손에서 부터 공구의 기하학적 형태가 크게 변하지 않는 작은 파손등 파손의 크기와 파손부위에 따른 신호의 형태를 조사하고자 한다. 그 방법으로서 가공재료로서는 SM45C강(steel)과 열처리한 SM45C강을 이용하였다. 공구파손에 따른 AE신호와 절삭력신호의 변화를 분석하기 위하여, AE신호의 경우는 RMS값을 택하고 그 진폭의 갑작스런 변화와 평균 레벨의 변화를 이용하여 파손의 순간 을 감지하였고, 절삭력의 경우에는 절삭력의 주분력, 이송분력 그리고 배분력의 변화 형태를 이용하여 공구의 이상상태를 알 수 있었으며, 이 두 신호의 변화를 동시에 관 찰함으로써 임의의 가공조건에서 공구의 파손을 감지할 수 있는 알고리즘 개발의 기준 을 마련할 수 있었다.

• 대한기계학회논문집
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• 제16권1호
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• pp.156-161
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• 1992

본 연구에서는 이송축 직류 서보 모터의 전류신호와 NC정보를 이용해서 선삭 가공상태를 감시하는 시스템을 개발하였다. 모터 전류는 가공 부하의 상태를 잘 나 타내며, NC 장치에 내장되어 있기 때문에 신호 검출을 위한 별도의 센서가 필요 없어 서 공구가 수시로 바뀌는 NC작업 감시를 위한 유효한 신호이다. 또 NC 정보로부터 작업을 예측함으로써 감시 대상을 명확히 하고 신뢰성을 높이고자 하였다. 전체적인 감시 시스템의 프로그래밍 언어로는 C를 사용하여, 실시간 감시처리를 가능하게 하였 다.

• 한국정밀공학회지
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• 제15권1호
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• pp.117-129
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• 1998

Micro-hole drilling (holes less than 0.5 mm in diameter with aspect ratio larger than 10) is recently having more attention in a wide spectrum of precision production industries. Alternative methods such as EDM. laser drilling, etc. can sometimes replace the mechanical micro-hole drilling but are not acceptable in PCB manufacture because of the inferior hole quality and accuracy. The major difficulties in micro-hole drilling are related to small signal to noise ratios, wandering motions of the inlet stage, high aspect ratios, high temperatures and so forth. Of all the difficulties. the most undesirable one is the increase of drilling force as the drill proceeds deeper into the hole. This is caused mainly from the chip effects. Peck-drilling is thus widely used for deep hole drilling despite that it suffers from low productivity. In the paper, a method of cutting force regulation is proposed to achieve continuous drilling. A PD and a sliding mode control algorithms were implemented through controlling the spindle rotating frequency. Experimental results show that the sliding mode control reduces the nominal cutting force and the variation of the cutting force better than the PD control. The advantages of the regulation, such as increase of drill life, fast stabilization of a wandering motion, and the precise positioning of the hole are verified in experiment.

• 오토저널
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• 제8권3호
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• pp.28-36
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• 1986

This study was investigated the feasibility of AE application on in-process detection of tool fracture and chipping. Carbon steel SM45C workpiece with longitudinal slots was turned interruptedly on a lathe. AE RMS signal at tool fracture was observed and also the tangential force and the feed observed at the time of tool fracture, the levels of tangential force and the feed force at the time of fracture decrease considerably. In chipping, high level AE signal was observed but there were no changes of cutting force. Peak AE RMS squared is proportional to the area of tool fracture and resultant force. Fracture model of tool fracture is proposed as $V_{p}$ = $C_{1}$ $E_{1}$F(.DELTA. A)$_{0.5}$ and peak AE RMS shows strong correlation with the fracture parameter F(.DELTA.A)$^{0.5}$.

• 기술사
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• 제21권4호
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• pp.6-11
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• 1988

The study on the progress of automatic machining system has been active centering at the CNC machine tools recently to lead the applied production technology like unmaned machining to the practical level, and to make these application more efficient, they require detective method for tool wear and breakage while machining. In this study chiefly on turning, first derive cutting force about the tool surface by the cutting resistant sensor and with which change into electric signal and compare with the standards to make the tool life detection system to let know the tool life and study its application; the cutting resistance detected by the cutting resistant sensor has increased to the level of standards, the measuring system which can decide whether we change tools on the basis of comperative circuit is shown to be very reliable model for cutting tool life detection system.