Paper Title:
Research on Surface Roughness Prediction Model for High-Speed Milling Inclined Plane of Hardened Steel
  Abstract

As the factors influencing the workpiece surface roughness is complexity and uncertainty, according to orthogonal experimental results, the paper established Empirical regression prediction model and generalized regression neural networks (GRNN) for prediction of surface roughness when machining inclined plane of hardened steel in high speed , moreover, compared their prediction errors. The results show that GRNN model has better prediction accuracy than empirical regression prediction model and can be better used to control the surface roughness dynamically.

  Info
Periodical
Advanced Materials Research (Volumes 97-101)
Edited by
Zhengyi Jiang and Chunliang Zhang
Pages
2044-2048
DOI
10.4028/www.scientific.net/AMR.97-101.2044
Citation
Y. L. Chen, B. L. Zhang, W. R. Long, H. Xu, "Research on Surface Roughness Prediction Model for High-Speed Milling Inclined Plane of Hardened Steel", Advanced Materials Research, Vols. 97-101, pp. 2044-2048, 2010
Online since
March 2010
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$32.00
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