A Prediction Model for Surface Roughness in Milling Based on Projection Pursuit Regression

Abstract:

A novel prediction model for surface roughness based on Projection Pursuit Regression was proposed in this paper. Based on the new model, the effects of milling parameters on surface roughness in milling can be predicted, and the predicted value of surface roughness in the whole working range can be reached with the limited test data, thus the variation law of quality of machined surface following milling parameters can be obtained. Compared with the least square support vector machine, it can be revealed that on the base of the same samples, the construction speed of this Projection Pursuit Regression is 1~2 higher in order of magnitude than that of the least square support vector machine, while the prediction errors are 40 % of the latter. Thus, the prediction model based on Projection Pursuit Regression can be established fast and be forecasted in high-precision, it is suitable for prediction of surface roughness.

• Periodical: Applied Mechanics and Materials (Volume 312)
• Pages: 143-147
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.312.143
• Online since: February 2013
• Authors: Xue Qin Pan, Na Zhu, Yu Cai Dong, Cui Xiang Liu, Min Lin, Xiao Yan Wang
• Keywords: Milling, Projection Pursuit Regression, Surface Roughness (SR)

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