• 제목/요약/키워드: Monitoring tool

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티타늄 합금의 슬롯가공에서 엔드밀 공구마멸 감시 (Tool wear monitoring of end mill in slot machining of titanium alloy)

  • 하건호;구세진;김정석;양순철
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.101-104
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    • 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.

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밀링공구의 마모 감시에 관한 연구 (A Study on the monitoring of tool wear in face milling operation)

    • 한국생산제조학회지
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    • 제7권1호
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    • pp.69-74
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    • 1998
  • In order to monitor the tool wear in milling operation, cutting force is measured as the tool wear increased. The digital signal processing methods are used to detect the tool wear . As AR parameter extract the feature of tool wear , it can be used as input parameter of pattern classifier. The FFT monitor the tool wear exactly , but it can not do real time signal processing. The band energy method can be used to real time monitoring of tool wear ,but int can degrade the exact monitoring.

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하이브리드 방식의 절삭력 평준화를 통한 CNC 엔드 밀링에서의 공구 마모 모니터링 시스템 (Tool Wear Monitoring System in CNC End Milling using Hybrid Approach to Cutting Force Regulation)

  • 이강재;양민양
    • 한국기계가공학회지
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    • 제3권4호
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    • pp.20-29
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    • 2004
  • A Tool wear monitoring system is indispensable for better machining productivity with guarantee of machining safety by informing the tool changing time in automated and unmanned CNC machining. Different from monitoring using other signals, the monitoring of spindle current has been used without requiring additional sensors on machine tools. For the reliable tool wear monitoring, current signal only of tool wear should be extracted from other parameters to avoid exhaustive analyses on signals in which all parameters are fused. In this paper, influences of force components of parameters on measured spindle current are investigated and a hybrid approach to cutting force regulation is employed for tool wear signal extraction in the spindle current. Finally, wear levels are verified with experimental results by means of real-time feedrate aspects changed to regulate the force component of tool wear.

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소규모 SMP 클러스터 시스템 모니터링 개발 (Development of Monitoring Tool for Small SMP Cluster System)

  • 성진우;이영주;최윤근;박찬열
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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    • pp.535-538
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    • 2007
  • 클러스터 시스템을 관리하기 위하여 모니터링 툴(S/W)이 필요하지만, 소규모 클러스터 시스템에 적합하고 관리자가 필요로 하는 기능을 갖춘 모니터링 툴을 결정하는 것은 쉽지가 않다. 본 문서는 인피니밴드 네트워크 스위치를 사용한 소규모 SMP 클러스터 시스템을 위하여 개발한 모니터링 툴의 설계와 구현 내용을 기술하였다. 모니터링 툴의 기능은 계산노드, 인피니밴드 스위치 그리고 작업관리 스케쥴러(PBS)의 작업을 모니터링한다.

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신경회로망을 이용한 원격모니터링을 위한 가공공정의 공구마모와 표면조도에 관한 연구 (A Study on the Tool Wear and Surface Roughness in Cutting Processes for a Neural-Network-Based Remote Monitoring system)

  • 권정희;장우일;정성현;김도언;홍대선
    • 한국생산제조학회지
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    • 제21권1호
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    • pp.33-39
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    • 2012
  • The tool wear and failure in automatic production system directly influences the quality and productivity of a product, thus it is essential to monitor the tool state in real time. For such purpose, an ART2-based remote monitoring system has been developed to predict the appropriate tool change time in accordance with the tool wear, and this study aims to experimently find the relationship between the tool wear and the monitoring signals in cutting processes. Also, the roughness of workpiece according to the wool wear is examined. Here, the tool wear is indirectly monitored by signals from a vibration senor attached to a machining center. and the wear dimension is measured by a microscope at the start, midways and the end of a cutting process. A series of experiments are carried out with various feedrates and spindle speeds, and the results show that the sensor signal properly represents the degree of wear of a tool being used, and the roughnesses measured has direct relation with the tool wear dimension. Thus, it is concluded that the monitoring signals from the vibration sensor can be used as a useful measure for the tool wear monitoring.

Tool-Setup Monitoring of High Speed Precision Machining Tool

  • Park, Kyoung-Taik;Shin, Young-Jae;Kang, Byung-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.956-959
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    • 2004
  • Recently the monitoring system of tool setting in high speed precision machining center is required for manufacturing products that have highly complex and small shape, high precision and high function. It is very important to reduce time to setup tool in order to improve the machining precision and the productivity and to protect the breakage of cutting tool as the shape of product is smaller and more complex. Generally, the combination of errors that geometrical clamping error of fixing tool at the spindle of machining tool and the asynchronized error of driving mechanism causes that the run-out of tool reaches to 3$^{\sim}$20 times of the thickness of cutting chip. And also the run-out is occurred by the misalignment between axis of tool shank and axis of spindle and spindle bearing in high speed rotation. Generally, high speed machining is considered when the rotating speed is more than 8,000 rpm. At that time, the life time of tool is reduced to about 50% and the roughness of machining surface is worse as the run-out is increased to 10 micron. The life time of tool could be increased by making monitoring of tool-setup easy, quick and precise in high speed machining tool. This means the consumption of tool is much more reduced. And also it reduces the manufacturing cost and increases the productivity by reducing the tool-setup time of operator. In this study, in order to establish the concept of tool-setup monitoring the measuring method of the geometrical error of tool system is studied when the spindle is stopped. And also the measuring method of run-out, dynamic error of tool system, is studied when the spindle is rotated in 8,000${\sim}$60,000 rpm. The dynamic phenomena of tool-setup are analyzed by implementing the monitoring system of rotating tool system and the non-contact measuring system of micro displacement in high speed.

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환경영향을 최소화한 비전 시스템을 이용한 미세공구의 상태 감시 기술 (Tool Monitoring System using Vision System with Minimizing External Condition)

  • 김선호;백운보
    • 한국기계가공학회지
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    • 제11권5호
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    • pp.142-147
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    • 2012
  • Machining tool conditions directly affect to quality of product and productivity of manufacturing. Many researches performed for tool condition monitoring in machining process to improve quality and productivity. Conventional methods use characteristics of signal for cutting force, motor current consumption, vibration of machine tools and machining sound. Recently, diameter of machining tool is become smaller for minimizing of mechanical parts. Tool condition monitoring using conventional methods are relatively difficult because micro machining using small diameter tool has low machining load and high cutting speed. These days, the direct monitoring for tool conditions using vision system is performed actively. But, vision system is affected by external conditions such as back ground of image and illumination. In this study, minimizing technology of external conditions using distribution analysis of image data are developed in micro machining using small diameter drill and tap. The image data is gathered from vision system. Several sets of experiment results are performed to verify the characteristics of the proposed machining technology.

엔드밀링 가동시 절삭력 신호와 공구마모에 대한 실험적 연구 (An Experimental Study on Cutting Force Signal and Tool Wear in End Milling)

  • 박철기
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1998년도 춘계학술대회 논문집
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    • pp.30-34
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    • 1998
  • In-process monitoring of cutting conditions and tool wear is important for improving productivity. This paper is concerned with on-line monitoring of tool wear and cutting force in end milling operation. The experimental study deals with the relations between flank wear and cutting force signal. Tool wear is detected by monitoring of cutting signal. A monitoring procedure is shown in this paper. The influence of flank wear on cutting signal activity was examined. The results are presented in the form of graphs. The analysis of the cutting signal and flank wear curves provides useful indicators of unacceptable wear development in the tool.

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AE센서를 이용한 고속 탭핑용 공구 모니터링에 관한 연구 (A Study on Tool Monitoring for High Speed Tapping using AE Signal)

  • 김용규;이돈진;김선호;안중환
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 추계학술대회 논문집
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    • pp.315-318
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    • 1997
  • In terms of productivity, the speed of machining process has been increasing in most of engineering part. But the tapping process does not reach at enough level compared with other machining processes because of its complicate cutting mechanism. In the high speed tapping process, the one of important elements is tool monitoring system to prevent tool breakage. This paper describes tool monitoring system by acoustic emission(AE) in the tapping process. We used 2 types of AE sensors in this test. The one is commercial sensor which is used in other machining monitoring system like polishing and the other is a self-fabricated sensor for this test. In this test we purpose to find out the frequency of AE signal in tapping process and verify the possibility of applying AE sensor in in-process tapping monitoring system. Also grasp of characteristic of tapping process by AE signal is handled.

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시계열 모델과 프랙탈 해석을 이용한 공구마멸 감시 (Tool Wear Monitoring using Time Series Model and Fractal Analysis)

  • 최성필;강명창;이득우;김정석
    • 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.

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