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

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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.

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Periodical:

Advanced Materials Research (Volumes 97-101)

Pages:

2044-2048

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.97-101.2044

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Online since:

March 2010

Authors:

Yuan Ling Chen, Bao Lei Zhang, Wei Ren Long, Hua Xu

Keywords:

Empirical Regression, GRNN, Hardened Steel, Prediction, Surface Roughness (SR)

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© 2010 Trans Tech Publications Ltd. All Rights Reserved

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