Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Burr Classification Using Acoustic Emission

음향방출을 이용한 버 유형 분류

  • Kim, Pil-Jae (Dept. of Precision Mechanical Engineering, Hanyang University) ;
  • Lee, Seoung-Hwan (Dept. of Mechanical Engineering, Hanyang University)
  • 김필재 (한양대학교 대학원 정밀기계공학과) ;
  • 이성환 (한양대학교 기계공학과)
  • Published : 2002.02.01
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Abstract

A number of experimental studies on burr formation in face milling operations have been pursued. They usually focus on machining parameters such as depth of cut, leed rate, spindle speed and in-plane exit angle. But it if difficult to set the correlation between burrs and the parameters on burr when such parameters are considered at the same time. Therefore, in this paper, acoustic emission (AE) is considered as an alternate way to predict burr types regardless of machining conditions. AE signals during face milling were sampled and processed, then fed into an artificial neural network to classify burr types \\\"on-line\\\".\\\".uot;.

Keywords

References

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