欢迎访问机床与液压官方网站!

咨询热线:020-32385312 32385313 RSS EMAIL-ALERT
神经网络PID算法在漆包线检测仪中的应用
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

湖南省自然科学基金项目(2020JJ7088);国家自然科学基金面上项目(51677063)


Application of Neural Network PID Algorithm in the Enameled Wire Detection Instrument
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为检测漆包线的热性能,设计了温度控制系统。利用BP神经网络在线修正PID参数,从而获取最优的一组参数,并将BP-PID控制算法应用于该温控系统。利用MATLAB进行仿真试验,验证了该控制系统能达到较好的控制效果。利用漆包线检测仪进行实物试验,结果表明:当控制温度为120 ℃时,该控制方式与传统PID控制相比具有更好的控温效果,超调率小于4%、稳态精度小于 2 ℃,达到了预期目的

    Abstract:

    In order to detect the thermal performance of the enameled wire, a temperature control system was designed. BP neural network was used to correct the PID parameters online to obtain the optimal parameters, and BP-PID control algorithm was applied to the temperature control system.The simulation experiment was carried out by using MATLAB, and the experimental results verified that the control system could achieve better control effect. Enamelled wire detectors were used for the physical experiment. The results show that when the control temperature is 120 ℃, compared with the traditional PID control, the control mode has better temperature control effect, the overshoot rate is less than 4%, the steadystate precision is less than ±2 ℃, reaching the expected goal.

    参考文献
    相似文献
    引证文献
引用本文

雷翔霄,徐立娟.神经网络PID算法在漆包线检测仪中的应用[J].机床与液压,2020,48(19):104-107.
LEI Xiangxiao, XU Lijuan. Application of Neural Network PID Algorithm in the Enameled Wire Detection Instrument[J]. Machine Tool & Hydraulics,2020,48(19):104-107

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2021-02-20
  • 出版日期: