Paper Title:
Grinding Acoustic Emission Classification in Terms of Mechanical Behaviours
  Abstract

The material removal in grinding involves rubbing, ploughing and cutting. For grinding process monitoring, it is important to identify the effects of these different phenomena experienced during grinding. A fundamental investigation has been made with single grit cutting tests. Acoustic Emission (AE) signals would give the information relating to the groove profile in terms of material removal and deformation. A combination of filters, Short-Time Fourier Transform (STFT), Wavelets Transform (WT), statistical windowing of the WT with the kurtosis, variance, skew, mean and time constant measurements provided the principle components for classifying the different grinding phenomena. Identification of different grinding phenomena was achieved from the principle components being trained and tested against a Neural Network (NN) representation.

  Info
Periodical
Edited by
Dongming Guo, Tsunemoto Kuriyagawa, Jun Wang and Jun’ichi Tamaki
Pages
15-20
DOI
10.4028/www.scientific.net/KEM.329.15
Citation
X. Chen, J. Griffin, "Grinding Acoustic Emission Classification in Terms of Mechanical Behaviours", Key Engineering Materials, Vol. 329, pp. 15-20, 2007
Online since
January 2007
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$32.00
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