• 제목/요약/키워드: Abnormal State of Drilling

검색결과 10건 처리시간 0.033초

드릴 가공된 구멍의 상태 검출에 관한 연구 (A Study on the Detection of the Drilled Hole State In Drilling)

  • 신형곤;김태영
    • 한국공작기계학회논문집
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    • 제12권3호
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    • pp.8-16
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    • 2003
  • Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

드릴링시 가공이상상태의 온라인 검출에 관한 연구 (A Study on The On-line Detection of the Abnormal State in Drilling.)

  • 신형곤;박문수;김민호;김태영
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2002년도 춘계학술대회 논문집
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    • pp.1038-1042
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    • 2002
  • Monitoring of the drill wear and hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process, and provide a relatively easy way to monitor a machining process for industrial application. For this advantage, AE signal is used to estimate the abnormal state. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so on, but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality As the results of this experiment, AE RMS signal and measurements by vision system are shown the similar tendency as abnormal state of drilling. And detection of the abnormal states using BPNs was achieved 96.4% reliability.

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열연강판의 드릴링시 공구의 이상상태 검출에 관한 연구 (A Study on the Detection of the Abnormal Tool State in Drilling of Hot-rolled High Strength Steel)

  • 신형곤;김민호;김태영
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 추계학술대회 논문집
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    • pp.888-891
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    • 2000
  • Drilling is one of the most important operations in machining industry and usually the most efficient and economical method of cutting a hole in metal. From automobile parts to aircraft components, almost every manufactured product requires that holes are to be drilled for the purpose of assembly, creation of fluid passages, and so on. It is therefore desirable to monitor drill wear and hole quality changes during the hole drilling process. One important aspect in controlling the drilling process is drill wear status monitoring. With the monitoring, we may decide on optimal timing for tool change. The necessity of the detection of tool wear, fracture and the abnormal tool state has been emphasized in the machining process. Accordingly, this paper deals with the cutting characteristics of the hot-rolled high strength steels using common HSS drill. The performance variables include drill wear data obtained from drilling experiments conducted on the workpiece. The results are obtained from monitoring of the cutting force and Acoustic Emission (AE) signals, and from the detection of the abnormal tool state with the computer vision system.

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신경망에 의한 공구 이상상태 검출에 관한 연구 (A Study on the Detection of the Abnormal Tool State for Neural Network in Drilling)

  • 신형곤;김태영
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 추계학술대회논문집A
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    • pp.821-826
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    • 2001
  • Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. Accordingly, this paper deals with Basic system and Online system. Basic system comprised of spindle rotational speed, feed rates, thrust, torque and flank wear measured tool microscope. Online system comprised of spindle rotational speed, feed rates, AE signal, flank wear area measured computer vision. On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

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드릴가공시 신경망에 의한 공구 이상상태 검출에 관한 연구 (A Study on the Detection of the Abnormal Tool State for Neural Network in Drilling)

  • 신형곤;김민호;김태영;김대성
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2001년도 춘계학술대회 논문집
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    • pp.1021-1024
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    • 2001
  • Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. In this paper, the vision system of the sensing methods of drill flank wear on the basis of image processing is used to detect the wear pattern by non-contact and direct method and get the reliable wear information about drill. In image processing of acquired image, median filter is applied for noise removal. The vision flank wear area of the drill was measured. Backpropagation neural networks (BPns) were used for no-line detection of drill wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, thrust and torque signals. The output was the drill wear state which was either usable or failure. Drilling experiments with various spindle rotational speed and feed rates were carried out. The learning process was peformed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

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모터전류를 이용한 드릴가공에서의 절삭이상상태 감시 시스템 (Monitoring System for Abnormal Cutting States in the Drilling Operation using Motor Current)

  • 김화영;안중환
    • 한국정밀공학회지
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    • 제12권5호
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    • pp.98-107
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    • 1995
  • The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

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예측감시 시스템에 의한 드릴의 마멸검출에 관한 연구 (A Study on the Wear Detection of Drill State for Prediction Monitoring System)

  • 신형곤;김태영
    • 한국공작기계학회논문집
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    • 제11권2호
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    • pp.103-111
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    • 2002
  • Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

ADI재의 드릴가공시 절삭저항 및 AE신호에 의한 공구마멸상해의 검출 (Monitoring of Tool Wear Condition by Cutting Resistance and AE Signal in Drilling ADI Material.)

  • 유경곤;전태옥;박홍식
    • 한국정밀공학회지
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    • 제15권11호
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    • pp.32-38
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    • 1998
  • For the purpose of monitoring the abnormal state in proportion to cutting in automatic production process, the 3 kinds of specimens different from mechanical properties by austempering through temperature variation were manufactured, and the effects of tool wear on thrust and AE RMS was analyzed with sequential drilling in in-process. When the ADI specimens were drilled, the relationship of thrust and AE RMS with flank wear was studied through experiments, and it is confirmed that the reliable wear state is able to be monitored by using these signals. It was shown that thrust and AE RMS increased slowly till flank wear reached to V$_{B}$ = 0.25mm, and they increased steeply over the value. The effective tool exchange time was able to be pre-estimated by using this fact. It was validated that the tool breakage was able to be detected on the real time by monitoring in in-process.s.

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공작기계 지능화를 위한 다중 감시 시스템의 개발-드릴가공에의 적용- (Development of a Multiple Monitioring System for Intelligence of a Machine Tool -Application to Drilling Process-)

  • 김화영;안중환
    • 한국정밀공학회지
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    • 제10권4호
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    • pp.142-151
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    • 1993
  • An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

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윤활유 오염과 디젤엔진의 크랭크핀 이상마모에 대한 원인 규명 (Root cause analysis of the abnormal wear on diesel engine crankpin and lubricant contamination)

  • 서정우;박동희
    • Journal of Advanced Marine Engineering and Technology
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    • 제38권7호
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    • pp.854-867
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    • 2014
  • 지속적인 유가의 상승에 따라 국제 석유 자본들의 유전개발에 대한 투자가 활발하고 지속적으로 증가하고 있는 추세에 있다. 최근 5년 동안(2008~2013)에 인도된 드릴쉽(drill-ship)은 67척으로 그 이전 30년 동안에 인도된 척수의 두 배에 이른다. 그리고 최근에는 3,000 m 내외의 심해유전 개발이 증가하고 있다. 이에 따라 시추 장비와 시스템이 대형화 추세에 있으며, 이들의 운전을 위한 디젤발전기의 용량이 증가하였다. 디젤발전기 용량은 일반 상선과는 달리 고출력 및 고전압이 요구되며, 이를 충족시키기 위하여 V-type 320 mm 실린더 내경의 고출력 엔진에 대한 수요가 증가하게 되었다. 드릴쉽의 경우 일반 상선 대비 선박건조 기간이 길어짐에 따라 커미셔닝 기간 중 장시간 저 부하 운전이 불가피하여 엔진 윤활유 관리의 중요성이 대두되었다. 최근에는 선박인도 전 크랭크핀에 캠마모(Cam wear)와 같은 이상마모가 발생하였으며 시리즈 호선 및 관련 호선들에 대한 크랭크핀의 전수 검사 결과 정도의 차이가 있었으나 모두 크랭크핀에 이상마모가 발생한 것이 확인되었다. 본 논문은 실제 호선에 적용된 엔진 크랭크핀의 이상마모 발생 원인에 대해 이상마모 메커니즘 분석과 실증결과 분석을 통하여 재발방지를 위한 대책 방안에 대하여 논하였다.