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

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 Ra. 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 Ra with a mean squared error 5.46％, was presented.

关键词： Surface roughness Artificial neural network (ANN) Free machining steel

作者: X.J. Cai Z.Q. Liu Q.C. Wang S. Han Q.L. An M. Chen

作者单位: School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240 China

会议类型: 国际会议

会议名称: The 4th International Conference on High Speed Machining(第四届高速加工国际会议 ICHSM2010)

会议地点: 武汉

会议语种:英文

页码: 535-541

在线出版日期: 2011-05-28（万方平台首次上网日期，不代表论文的发表时间）