论文信息 - Study on Dynamic Machining Performance of Machine Tool Based on BP Network

Study on Dynamic Machining Performance of Machine Tool Based on BP Network

Abstract It is analyzed on the relationship of the vibration and the machining performance of machine tool in this paper, and estimate the dynamics machining performance of machine tool on line based on BP (Back Propagation) network. Clustering is used to process data in order to reduce the number of data. Calculate speed of estimating system is increased by this method of data processing and satisfied the need of estimating on line. The 718 CNC is simulated with 25 groups of faulty state data and 25 groups of normal state data, and the simulation results show that the system can accurately estimate the dynamic machining performance of machine tool. The estimated method is very important to maintenance for machine tool.

Hongli Gao | Haifeng Huang | Xiaochen Zhang | Mingheng Xu | Yingsong Chen

[1] Dipti Srinivasan,et al. A B-spline network based neural controller for power electronic applications , 2010, Neurocomputing.

[2] Leandro dos Santos Coelho,et al. B-spline neural network design using improved differential evolution for identification of an experimental nonlinear process , 2008, Appl. Soft Comput..

[3] Sukhan Lee,et al. A Gaussian potential function network with hierarchically self-organizing learning , 1991, Neural Networks.

[4] Liang Guo,et al. Life prediction of CNC linear rolling guide based on DFNN performance degradation model , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.