Research on Thermal Error Modeling of NC Machine Tool Based on BP Neural Networks

Qian Jian Guo; X.N. Qi

doi:10.4028/www.scientific.net/MSF.626-627.135

Paper Titles

A Novel Design of Calibration Equipment for 6-Component Huge Force Sensor and Coupling Modification
p.111

Tool-Life Optimization in High-Speed Milling of Aeronautical Aluminum Alloy 7050-T7451
p.117

Experimental Research on Surface Roughness in High Speed Milling of Complex Surface Mold Steel
p.123

Design Optimization of Cutting Parameters Using Taguchi Method and ANOVA during High-Speed Machining Hardened H13 Steel
p.129

Research on Thermal Error Modeling of NC Machine Tool Based on BP Neural Networks
p.135

Folding Method and Controlling Tactics of the Tire Building Hub Based on the Parallel Mechanism
p.141

The Study on the Surface Abrasion about Wafer Final Polishing
p.147

Study on the AE Signal Based Grinding Contact Detection Method for Thin-Walled Ceramic Materials
p.153

Analysis and Measurement of Effective Flow-Rate in Flood Grinding
p.159

HomeMaterials Science ForumMaterials Science Forum Vols. 626-627Research on Thermal Error Modeling of NC Machine...

Research on Thermal Error Modeling of NC Machine Tool Based on BP Neural Networks

Abstract:

Through analysis of the thermal errors affected NC machine tool, a new prediction model based on BP neural networks is presented, and ant colony algorithm is applied to train the weights of neural network model. Finally, thermal error compensation experiment is implemented, and the thermal error is reduced from 35μm to 6μm. The result shows that the local minimum problem of BP neural network is overcome, and the model accuracy is improved.