Journal of Shanghai Jiaotong University ›› 2014, Vol. 48 ›› Issue (1): 22-26.

• Mechanical instrumentation engineering • Previous Articles     Next Articles

AVQ Clustering Algorithm and OIF-Elman Neural Network for Machine Tool Thermal Error

ZHU Xiaolong,YANG Jianguo,DAI Guisong
  

  1. (School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2013-03-13

Abstract:

An adaptive vector quantization (AVQ) network clustering algorithm based on feed-forward neural network for the selection of temperature measuring points was proposed in thermal error compensation on machine tools. The method reduces the measuring points from 18 to 3, when adopted on a machining center. Then the relationship between thermal error and key temperature measuring points was established based on the output-input feedback Elman neural network model. The experimental results show that the method proposed can effectively eliminate the coupling among temperature measuring points and improve the accuracy and robustness of the thermal error model.

Key words: computer numerical control(CNC) machine tool, adaptive vector quantization (AVQ) network, outputinput feedback Elman neural network, thermal error modeling

CLC Number: