• CN:11-2187/TH
  • ISSN:0577-6686

›› 2001, Vol. 37 ›› Issue (6): 102-105.

• 论文 • 上一篇    下一篇

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利用神经网络控制技术消除车削过程自激振荡的仿真研究

王新晴;王耀华;严骏   

  1. 解放军理工大学工程兵工程学院
  • 发布日期:2001-06-15

SIMULATIVE STUDY ON ELIMINATING OF SELF-EXCITED OSCILLATION IN TURNING PROCESS VIA NEURAL NETWORK CONTROL TECHNOLOGY

Wang Xinqing;Wang Yaohua;Yan Jun   

  1. PLA University of Science and Technology
  • Published:2001-06-15

摘要: 车削过程自激振荡是一种以残留振痕作为机械延时反馈造成的动态失稳现象,消除这一现象是机械加工过程中的技术关键之一。将人工神经网络理论引入非线性或不稳定系统行为的控制,即可形成一种基于神经网络控制技术的消除车削过程自激振荡的新方法。仿真结果表明,该方法在消除残留振痕引起的车削再生颤振,提高车削稳定性方面具有特殊作用。

关键词: 神经网络, 再生颤振, 自激振荡

Abstract: Self-excited oscillation in turning process is a kind of unstable phenomenon resulting from former vibration trace. Eliminating of the phenomenon is a key technology in cutting process. Back propagation neural network (BP network) is introduced to control behaviors of nonlinear or unstable system. According to neural network control technology a new technology for the elimination of self-excited oscillation in turning process is put forward. Numerical simulation examples show that such technology plays special roles in the eliminating of self-excited oscillation and the control of turning stability.

Key words: Neural network, Regenerative chatter, Self-excited oscillation

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