Paper Title:
Surface Roughness Prediction of High Speed Milling Based on Back Propagation Artificial Neural Network
  Abstract

Prediction of surface roughness is an important research for machining quality analysis. In order to predict surface roughness in machining, increasing productivity under ensuring milling, the artificial neural network is introduced into milling area. To build high-speed milling surface roughness prediction model using BP neural network. Prediction results are compared with experimental value, which shows that this method can achieve better prediction accuracy. It has certain significance for parameters selection of high-speed milling and quality control of the surface.

  Info
Periodical
Advanced Materials Research (Volumes 201-203)
Edited by
Daoguo Yang, Tianlong Gu, Huaiying Zhou, Jianmin Zeng and Zhengyi Jiang
Pages
696-699
DOI
10.4028/www.scientific.net/AMR.201-203.696
Citation
J. P. Hu, Y. Li, J. C. Zhang, "Surface Roughness Prediction of High Speed Milling Based on Back Propagation Artificial Neural Network", Advanced Materials Research, Vols. 201-203, pp. 696-699, 2011
Online since
February 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Chang Rong Li, Hao Wen Zhao, Qing Yin
Abstract:Reaction process of BOF steelmaking is a very complex physical chemistry process which is very difficult to describe linearity. The...
4446
Authors: Hui Zhen Yang, Wen Guang Zhao, Wei Chen, Xu Quan Chen
Chapter 8: System Modeling and Simulation
Abstract:Wavelet Neural Network (WNN) is a new form of neural network combined with the wavelet theory and artificial neural network. The wavelet...
4847
Authors: Lei Wang, Jiang Ning Gai
Chapter 3: Micro/Nano Materials
Abstract:In electrochemical machining (ECM) machining accuracy of workpieces is greatly influenced by many machining parameters. In this paper the BP...
375
Authors: Yi Hui Zhang, He Wang, Zhi Jian Hu, Meng Lin Zhang, Xiao Lu Gong, Cheng Xue Zhang
Chapter 3: Development and Utilization of Wind Energy
Abstract:Extreme learning machine (ELM) is a new and effective single-hidden layer feed forward neural network learning algorithm. Extreme learning...
564
Authors: Feng Wang, Zhi Zhong Tan, De You Liu, Xiang Dong Qian
Chapter 4: Pharmaceutical, Chemical and Energy Engineering
Abstract:This paper analyzes the importance of the wind farm wind speed prediction, as well as the different forecasting methods in various fields....
741