• 제목/요약/키워드: Tool wear monitoring

검색결과 137건 처리시간 0.025초

절삭력 신호특성과 히스토그램 분석에 의한 공구마모와 파손 진단 (Diagnosis of tool wear and fracture using cutting force signal characteristics and histogram analysis)

  • 정진용;유기현;서남섭
    • 한국정밀공학회지
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    • 제14권3호
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    • pp.75-81
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    • 1997
  • Automatic monitoring the cutting state is one of the important problems to increase the reliability of modern machining processes. In this study, cutting force signals were used in order to monitor the tool wear and fracture in the turning process. Turning experiments were performed using cemented carbide insert tools(K20) and STS304 steel as a workpiece. Cutting force signal characteristics and histogram analysis method were used to recognize the cutting states. It was found that tool wear and fracture can be diagnosed from the cutting force signal coefficient of variation(C.V.) and histogram analysis.

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알루미늄 홀 가공 하중 분석을 통한 펀치 마모수준 예측에 관한 연구 (A study on the prediction of punch wear level through analysis of piercing load of aluminum)

  • 전용준
    • Design & Manufacturing
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    • 제16권4호
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    • pp.46-51
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    • 2022
  • The piercing process of creating holes in sheet metals for mechanical fastening generates high shear force. Real-time monitoring technology could predict tool damage and product defects due to this severe condition, but there are few applications for piercing high-strength aluminum. In this study, we analyzed the load signal to predict the punch's wear level during the process with a piezoelectric sensor installed piercing tool. Experiments were conducted on Al6061 T6 with a thickness of 3.0 mm using piercing punches whose edge angle was controlled by reflecting the wear level. The piercing load increases proportionally with the level of tool wear. For example, the maximum piercing load of the wear-shaped punch with the tip angle controlled at 6 degrees increased by 14% compared to the normal-shaped punch under the typical clearance of 6.7% of the aluminum piercing tool. In addition, the tool wear level increased compression during the down-stroke, which is caused by lateral force due to the decrease in the diameter of pierced holes. Our study showed the predictability of the wear level of punches through the recognition of changes in characteristic elements of the load signal during the piercing process.

AE법에 의한 공구손상 및 수명의 감시기술에 관한 연구 (A Study on the Monitoring Technique in Tool Failure and Tool Life by AE Method)

  • 한응교;김기중
    • 한국정밀공학회지
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    • 제2권1호
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    • pp.62-71
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    • 1985
  • This is a study on the monitoring technique in tool failure and tool life by AE method. The relation between amplitude level of AE signal and flank wear width was studied by experiments. The relation between amplitude level of AE signal and tool life was also studied. As the result, it was observed that amplitude level of AE signal was only affected by cutting velocity. Amplitude level of AE signal was directly proportional to flank wear width and the increasing rate was related to cutting velocity. So, the relation between amplitude level of AE signal and tool life was represented as follow: $CT^n$ = $AE_{rms}$ where, n=0.35 C=9.5*$10^{-2}$

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입자 유형별 형상추출에 의한 마모입자 자동인식에 관한 연구 (A study on automatic wear debris recognition by using particle feature extraction)

  • 장래혁;윤의성;공호성
    • 한국윤활학회:학술대회논문집
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    • 한국윤활학회 1998년도 제27회 춘계학술대회
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    • pp.314-320
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    • 1998
  • Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

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입자 유형별 형상추출에 의한 마모입자 자동인식에 관한 연구 (A Study on Automatic wear Debris Recognition by using Particle Feature Extraction)

  • 장래혁;윤의성;공호성
    • Tribology and Lubricants
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    • 제15권2호
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    • pp.206-211
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    • 1999
  • Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

선사가공에 절삭력을 이용한 공구마멸의 감지 (Detection of Tool Wear using Cutting Force Measurement in Turning)

  • 윤재웅;이권용;이수철;최종근
    • 한국공작기계학회논문집
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    • 제10권1호
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    • pp.1-9
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    • 2001
  • The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining system A major topic relevant to metal-cutting operations is monitoring toll wear, which affects process efficiency and product quality, and implementing automatic toll replacements. In this paper, the measurement of the cutting force components has been found to provide a method for an in-process detection of tool wear. The static com-ponents of cutting force have been used to detect flank wear. To eliminate the influence of variations in cutting conditions, tools, and workpiece materials, the force modeling is performed for various cutting conditions. The normalized force dis-parities are defined in this paper, and the relationships between normalized disparity and flank were are established. Final-ly, artificial neural network is used to learn these relationships and detect tool wear. According to proposed method, the static force components could provide the effective means to detect flank wear for varying cutting conditions in turning operation.

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Tool Condition Monitoring Based on Wavelet Transform

  • Doyoung Jeon;Lee, Gun;Kim, Kyungho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.95.5-95
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    • 2002
  • Tool condition monitoring is recognized important in CNC machining processes since the excessive wear or breakage of tool has to be noticed immediately in an automated manufacturing system to keep the quality and productivity. In this research, as an economic way of detecting the status of tool change, the wavelet transform has been applied to the measurement of spindle motor current. The energy of a specific level shows the difference between a normal tool and worn one. By setting a limit on the change of energy, it is possible to notify the time to inspect the tool.

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AE 센서를 이용한 CNC 공작기계의 절삭공구 마모에 관한 연구 (A Study on CNC Machine Tool Wear using AE Sensor)

  • 정수일;정재수;김광태
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2000년도 춘계학술대회
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    • pp.241-248
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    • 2000
  • Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automation system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

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AE 센서를 이용한 CNC 공작기계의 절삭공구 마모에 관한 연구 (A Study on CNC Machine Tool Wear using AE Sensor)

  • 정재수;김광태;정수일
    • 대한안전경영과학회지
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    • 제2권3호
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    • pp.185-195
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    • 2000
  • Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automatino system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

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음향주파수 분석에 의한 엔드밀의 마모상태 추정에 관한 연구 (A Study on the Wear Estimation of End Mill Using Sound Frequency Analysis)

  • 이창희;조택동
    • 대한기계학회논문집A
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    • 제27권8호
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    • pp.1287-1294
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    • 2003
  • The wear process of end mill is so complicated process that a more reliable technique is required for the monitoring and controlling the tool life and its performance. This research presents a new tool wear monitoring method based on the sound signal generated on the machining. The experiment carried out continuous-side-milling for 4 cases using the high-speed-steel end mill under wet condition. The sound pressure was measured at 0.5m from the cutting zone by a dynamic microphone, and was analyzed at frequency domain. As the cutter impacts the workpiece surface, a situation of farced vibration arises in which the dominant forcing frequency is equal to the tooth passing frequency of the cutter. The tooth passing frequency appears as a harmonics form, and end mill flank wear is related with the first harmonic. It is possible to detect end . mill flank wear. This paper proposed the new method of the end mill wear detection.