Prediction of Surface Roughness for HSM Based on BP Neural Network
Chen Ying, Sun Yanhong, Yang Zhengwen, Wu Guangdong
Available Online June 2016.
- https://doi.org/10.2991/icemc-17.2017.83How to use a DOI?
- Surface roughness; BP neural network; Cutting parametres; 5-axis machine; Toroidal cutter
- A predictive model is presented for the surface roughness in high-speed milling of P1.2738 (plastic die steel)based on BP Neural network. The data for establishing the model is derived from the experiment conducted on a high-speed 5-axis machining center by factorial design of experiments. Compared with measured data and data from regression analysis, the result of prediction using BP neural network indicates its feasibility, which provides reference for the optimization of cutting parameters.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Chen Ying AU - Sun Yanhong AU - Yang Zhengwen AU - Wu Guangdong PY - 2016/06 DA - 2016/06 TI - Prediction of Surface Roughness for HSM Based on BP Neural Network BT - Proceedings of the 7th International Conference on Education, Management, Information and Computer Science (ICEMC 2017) PB - Atlantis Press SP - 421 EP - 424 SN - 2352-538X UR - https://doi.org/10.2991/icemc-17.2017.83 DO - https://doi.org/10.2991/icemc-17.2017.83 ID - Ying2016/06 ER -