Study on Machine Accuracy of the Serial-Parallel Machine Tool Based on the BP Neural Network

摘要：

It were researched that the modeling methods of machine accuracy and the control techniques of the error compensation based on BP neural network(BPNN) for parallel machine tool(PMT)with five degrees of freedom(DOF). The samples are obtained to train the BP neural network which has good capacity for non- liner mapping, learning and generalization. The machine accuracy mathematics model is established for the error compensation, in order to study the nonlinear input and output problem of the parallel machine which difficultly modeling described. The trained neural network was applied to error compensation of PMT to realize modifying errors real-timely. Finally, simulation analysis was performed through the MATLAB software. The results expressed that the control strategies for error compensation were simple, efficient and practicable. Machine accuracy can be increased greatly after compensation.

关键词： BP neural network Parallel Machine Tool Error compensation Machine accuracy

作者: PEI Xuming LIU Jie ZHANG Chao

作者单位: ZhengZhou University of Light Industry, Zhengzhou, 450002, China

会议类型: 国际会议

会议名称: 第九届加工技术进展国际会议(9th International Conference on Progress of Machining Technology)

会议地点: 昆明

会议语种:英文

页码: 140-145

在线出版日期: 2009-04-25（万方平台首次上网日期，不代表论文的发表时间）