Surface Roughness Prediction in Turning of Free Machining Steel 1215 by Artificial Neural Network

被引：1

作者：

Cai, X. J. ^{[1
]}

Liu, Z. Q. ^{[1
]}

Wang, Q. C. ^{[1
]}

Han, S. ^{[1
]}

An, Q. L. ^{[1
]}

Chen, M. ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200240, Peoples R China

来源：

HIGH SPEED MACHINING | 2011年 / 188卷

关键词：

Surface roughness; Artificial neural network (ANN); Free machining steel;

D O I：

10.4028/www.scientific.net/AMR.188.535

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Surface roughness is a significant aspect of the surface integrity concept. It is efficient to predict the surface roughness in advance by a prediction model. In this study, artificial neural network is used to model the surface roughness in turning of free machining steel 1215. The inputs considered in the prediction ANN model were cutting speed, feed rate and depth of cut, and the output was R-a. Several feed-forward neural networks with different architectures were compared in terms of prediction accuracy, and then the best prediction model, a 3-4-1-1 ANN was capable of predicting R-a with a mean squared error 5.46%, was presented.

引用

页码：535 / 541

页数：7

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