Characterization of Magnetic Abrasive Finishing Using Sensor Fusion

센서 융합을 이용한 MAF 공정 특성 분석

  • 김설빔 (한양대학교 대학원 기계설계.메카트로닉스 시스템공학과) ;
  • 안병운 ;
  • 이성환 (한양대학교 기계공학과)
  • Published : 2009.05.01


In configuring an automated polishing system, a monitoring scheme to estimate the surface roughness is necessary. In this study, a precision polishing process, magnetic abrasive finishing (MAF), along with an in-process monitoring setup was investigated. A magnetic tooling is connected to a CNC machining to polish the surface of stavax(S136) die steel workpieces. During finishing experiments, both AE signals and force signals were sampled and analysed. The finishing results show that MAF has nano scale finishing capability (upto 8nm in surface roughness) and the sensor signals have strong correlations with the parameters such as gap between the tool and workpiece, feed rate and abrasive size. In addition, the signals were utilized as the input parameters of artificial neural networks to predict generated surface roughness. Among the three networks constructed -AE rms input, force input, AE+force input- the ANN with sensor fusion (AE+force) produced most stable results. From above, it has been shown that the proposed sensor fusion scheme is appropriate for the monitoring and prediction of the nano scale precision finishing process.


Acoustic Emission(AE);Surface Roughness;Magnetic Abrasive Finishing;Force Sensor;Artificial Neural Networks


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