Paper Title:
Dynamic Intelligent Prediction Control in Slender Cylindrical Grinding
  Abstract

A dynamic intelligent prediction control system is built in slender cylindrical grinding. Elman network is used in the dynamic size prediction control model, and the first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the size dynamic prediction accuracy. Moreover, a surface roughness equation with vibration data is proposed. Based the equation, the surface roughness dynamic fuzzy neural network prediction subsystem is built. Experiment verifies that the developed prediction control system is feasible and has high prediction and control accuracy.

  Info
Periodical
Key Engineering Materials (Volumes 359-360)
Edited by
Jiuhua Xu, Xipeng Xu, Guangqi Cai and Renke Kang
Pages
189-193
DOI
10.4028/www.scientific.net/KEM.359-360.189
Citation
N. Ding, X. M. Li, Y. Ding, G. F. Li, L. S. Wang, "Dynamic Intelligent Prediction Control in Slender Cylindrical Grinding ", Key Engineering Materials, Vols. 359-360, pp. 189-193, 2008
Online since
November 2007
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Price
$32.00
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