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

Abstract:

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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 et al., "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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Price:

$35.00

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