• 제목/요약/키워드: tool wear monitoring

검색결과 137건 처리시간 0.03초

복합가능형 절삭상태인식용 In-Process Sensor에 관한 연구 (A Study on In-Porcess Sensor for Recognizing Cutting Conditions)

  • 정의식;김영대;남궁석
    • 한국정밀공학회지
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    • 제7권2호
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    • pp.47-57
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    • 1990
  • In-process recognition of the cutting states is one of the very important technologies to increase the reliability of mordern machining process. In this study, practical methods which use the dynamic component of the cutting force are proposed to recognize cutting states (i.e. chip formation, tool wear, surface roughness) in turning process. The signal processing method developed in this study is efficient to measure the maximum amplitude of the dynamic component of cutting force which is closely related to the chip breaking (cut-off frequency : 80-500 Hz) and the approximately natural frequency of cutting tool (5, 000-8, 000 Hz). It can be clarified that the monitoring of the maximum apmlitude in the dynamic component of the cutting force enables the state of chip formation which chips can be easily hancled and the inferiority state of the machined surface to be recognized. The microcomputer in-process tool wear monitor- ing system introduced in this paper can detect the determination of the time to change cutting tool.

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마이크로 엔드밀링 공정의 절삭계수 모델링 및 최적 공정설계 (Modeling of Cutting Parameters and Optimal Process Design in Micro End-milling Processes)

  • 이광조;정성종
    • 한국생산제조학회지
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    • 제18권3호
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    • pp.261-269
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    • 2009
  • Micro end-milling process is applied to fabricate precision mechanical parts cost-effectively. It is a complex and time-consuming job to select optimal process conditions with high productivity and quality. To improve the productivity and quality of precision mechanical parts, micro end-mill wear and cutting force characteristics should be studied carefully. In this paper, high speed machining experiments are studied to construct the optimum process design as well as the mathematical modeling of tool wear and cutting force related to cutting parameters in micro ball end-milling processes. Cutting force and wear characteristics under various cutting conditions are investigated through the condition monitoring system and the design of experiment. In order to construct the cutting database, mathematical models for the flank wear and cutting force gradient are derived from the response surface method. Optimal milling conditions are extracted from the developed experimental models.

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C-means 알고리즘을 이용한 마이크로 엔드밀의 상태 감시 (Condition Monitoring of Micro Endmill using C-means Algorithm)

  • 권동희;정연식;강익수;김전하;김정석
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2005년도 춘계학술대회 논문집
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    • pp.162-167
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    • 2005
  • Recently, the advanced industries using micro parts are rapidly growing. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro to micro parts. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This study deals with condition monitoring using acoustic emission(AE) signal in the micro-grooving. First, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by using the fuzzy C-means algorithm, which is one of the methods to recognize data patterns. These result is effective monitoring method of micro endmill state by the AE sensing techniques which can be expected to be applicable to micro machining processes in the future.

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절삭조건에 따른 AE 신호의 거동 (A Behavior of AE Signal on the Cutting Conditons)

  • 원종식
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1997년도 추계학술대회 논문집
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    • pp.59-64
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    • 1997
  • This paper investigates the relationship between cutting conditions and Acoustic Emission(AE) signals; AEavg, AErms, AEmode, as the base working to monitor the tool wear with in-process. For this purpose, cutting tests were conducted on a CNC lathe with comprehensive cutting conditions.. It is known that AEavg and AErms are proportionaly increased as the increasing of cutting velocity and depth of cut respectively. It is also known that AEmode among three kinds of AE signals may be applied for in-process monitoring to make the self diagnosis system because of its stability to the variation of cutting condition.

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금형강의 고속가공시 공구상태의 감시 (Monitoring of tool conditions in high-speed machining of die material)

  • 허현;이기용;정융호;이득우;김정석;황경현
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.131-134
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    • 1995
  • The high efficiency and accuracy in machining the die material can be abtained in high speed machining, so it is necessary to analyze the mechanism of high speed cutting process : cutting force, flank wear. The tool dynomometer with high natural frequency is newly developed. With this device, the mechanism of high speed cutting process is investigated according to speed and feedate.

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AE 신호의 주파수분석에 의한 Chatter 진동의 감시 (Monitoring of Chatter Vibration by Frequency Analysis of AE Signals)

  • 조대현
    • 한국생산제조학회지
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    • 제9권5호
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    • pp.157-164
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    • 2000
  • A machine tool generally has some serious stability problems in the form of tool chatter during the cutting process. Chatter vibration deteriorates the surface finish, reduce tool and machine life, accelerates machine tool system component wear, and may lead to an unacceptable noise sound in the working environment. In this study, the behavior of spectral density of AE signal and principal cutting force signal in order to monitor the chatter vibration in the cutting process has been investigated. From the results, the reliability of proposed monitoring method has been confirmed.

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음향방출에 의한 드릴 마멸에 감시에 관한 연구 (A Study on In-Process Monitoring of Drill Wear by Acoustic Emission)

  • 윤종학
    • 한국생산제조학회지
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    • 제5권2호
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    • pp.38-45
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    • 1996
  • This study was focused on the prediction of the approprite tool life by clarifying the correlation between progressive drill wear and AE signal. on drilling SM45C the following results have been obtained; RMSAE, AE CUM-CNTS had a tendency to increase slowly according to wear size, at 1000rpm, 150mm/min However, these increased suddenly in the range of 0.20~0.22mm wear, about 102 holes and had a tendency to go up and down until the drilling was impossible. The sudden increase of AE signals shows that something is wrong and it is closely connected with drill wear and chipping. It also makes the working surface bad From the above results, AE signals could be used to monitor the drill's condition and to determine the right time to change tools.

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연삭동력을 이용한 숫돌수명 판정 (Determination of decision of wheel life using grinding power)

  • 이상태
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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    • pp.204-209
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    • 1999
  • The dressing time monitoring in cylindrical grinding is very important with respect to machining efficiency. Therefore, the purpose of this paper is to determine the wheel life by monitoring behavior of grinding power for Wa, 19A and GC. For this purpose, we investigated indirectly the attritious wear of grain edge, the loading of grinding wheel and the breakage of grain through the grinding power and the surface roughness under various grinding conditions. From obtained the results, the relationship between the wheel life and the average sectional chip area is examined to guide for the determination of dressing time.

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초경합금의 미세방전 드릴링에 관한 연구 (A Study on Micro ED-Drilling of cemented carbide)

  • 김창호;강수호
    • 한국기계가공학회지
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    • 제9권5호
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    • pp.1-6
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    • 2010
  • The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.