한국생산제조학회지 (Journal of the Korean Society of Manufacturing Technology Engineers)

  • 제21권4호
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  • Pages.601-607
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  • 2012
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  • 2508-5093(pISSN)
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  • 2508-5107(eISSN)
한국생산제조학회 (The Korean Society of Manufacturing Technology Engineers)
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AE 센서와 신경회로망을 이용한 NAK80 금형강의 자기연마 가공특성 모니터링

Surface Condition Monitoring in Magnetic Abrasive Polishing of NAK80 Using AE Sensor and Neural Network

  • 김광희 (부경대학교 기계자동차공학과) ;
  • 신창민 (부경대학교 기계공학과) ;
  • 김태완 (부경대학교 기계공학과) ;
  • 곽재섭 (부경대학교 기계공학과)
  • 투고 : 2011.12.15
  • 심사 : 2012.01.31
  • 발행 : 2012.08.15
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초록

The magnetic abrasive polishing (MAP), for online monitoring with AE sensor attachment, was performed in this study. To predict the surface roughness after the magnetic abrasive polishing of NAK80, the signal data acquired from the AE sensor were analyzed. A dimensionless coefficient, which consisted of average of AErms and standard deviation of AE signal, was defined as a characteristic of the MAP and a prediction model was obtained using least square method. A neural network, which had multiple input parameters from AE signals and polishing conditions, was applied for predicting the surface roughness. As a result of this study, it was seen that there was very close correlation between the AE signal and the surface roughness in the MAP. And then on-line prediction of the surface roughness after the MAP of the NAK80 was possible by the developed prediction model.

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참고문헌

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