Paper Title:
Research on the Machining Status Monitoring of CNC Machine Tools Based on Artificial Neural Network
  Abstract

Vibration acceleration and AE signal were analyzed in the time domain, and they sampled the mean value and mean value of energy. The two values were used as the basis of the state recognition and tool wear prediction. In Labview, the neural network model was established, and it had three-layer structure. the nonlinear mapping was realized between machining state and characteristic quantity. The outcome could show that the machining state was monitored by the neural network training.

  Info
Periodical
Chapter
Chapter 5: Advanced Manufacturing Technology
Edited by
Xiaodong Zhang, Zhijiu Ai, Prasad Yarlagadda and Yun-Hae Kim
Pages
685-688
DOI
10.4028/www.scientific.net/AMR.338.685
Citation
J. H. Li, Y. X. Liu, D. L. Yi, D. Q. Zhang, "Research on the Machining Status Monitoring of CNC Machine Tools Based on Artificial Neural Network", Advanced Materials Research, Vol. 338, pp. 685-688, 2011
Online since
September 2011
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Price
$32.00
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