Paper Title:
Study on the Application of the Combined Prediction Modeling Method to Thermal Error Modeling on NC Machine Tools
  Abstract

Due to the complexity of machine tool thermal errors affected by various factors, a new combining prediction model, based on the theory of gery system GM (1,1) model, is applied to the trend prediction of machine tool thermal errors. The degree of smoothness of primary data sequence is first improved by function transform method and sequentially grey system GM (1,1) model is established; second, time series analysis model is established by remnant sequence of GM (1,1) model to amend the precision of grey system GM (1,1) model. Thus, the precision of combining prediction model is further improved. Through the prediction study on thermal error modeling in a spot NC turning center, testing results showed that combining prediction model can highly improve machine tool’s prediction precision and make it more effective for real-time compensation of machine tool thermal error.

  Info
Periodical
Edited by
Dongming Guo, Tsunemoto Kuriyagawa, Jun Wang and Jun’ichi Tamaki
Pages
779-784
DOI
10.4028/www.scientific.net/KEM.329.779
Citation
Y.X. Li, J. G. Yang, Y. Y. Li, H.T. Zhang, G. Turyagyenda, "Study on the Application of the Combined Prediction Modeling Method to Thermal Error Modeling on NC Machine Tools", Key Engineering Materials, Vol. 329, pp. 779-784, 2007
Online since
January 2007
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