Spindle Thermal Error Optimization Modeling of a Five-axis Machine Tool
作者: Qianjian GUOShuo FANRufeng XUXiang CHENGGuoyong ZHAOJianguo YANG
作者单位: 1Shandong University of Technology
2Shanghai Jiao Tong University
刊名: Chinese Journal of Mechanical Engineering, 2017, Vol.30 (3), pp.746-753
来源数据库: Springer Nature Journal
DOI: 10.1007/s10033-017-0098-0
关键词: Five-axis machine toolArtificial bee colonyThermal error modelingArtificial neural network
原始语种摘要: Aiming at the problem of low machining accuracy and uncontrollable thermal errors of NC machine tools, spindle thermal error measurement, modeling and compensation of a two turntable five-axis machine tool are researched. Measurement experiment of heat sources and thermal errors are carried out, and GRA(grey relational analysis) method is introduced into the selection of temperature variables used for thermal error modeling. In order to analyze the influence of different heat sources on spindle thermal errors, an ANN (artificial neural network) model is presented, and ABC(artificial bee colony) algorithm is introduced to train the link weights of ANN, a new ABC-NN(Artificial bee colony-based neural network) modeling method is proposed and used in the prediction of spindle thermal errors....
全文获取路径: Springer Nature  (合作)
影响因子:0.263 (2012)

  • modeling 制祝型
  • machine 机器
  • thermal 热的
  • errors 错帐
  • neural 神经系统的
  • artificial 人为的
  • prediction 预报
  • tools 工具
  • ANN All Numeral Numbering
  • network 网络