›› 2015, Vol. 28 ›› Issue (7): 140-.

• 论文 • 上一篇    下一篇

基于图像处理的挤出胎面尺寸控制应用

唐勋俊   

  1. (桂林电子科技大学 电子工程与自动化学院,广西 桂林 541004)
  • 出版日期:2015-07-15 发布日期:2015-07-13
  • 作者简介:唐勋俊(1988—),男,硕士研究生。研究方向:工业智能控制。E-mail:504704056@qq.com
  • 基金资助:

    桂林电子科技大学研究生教育创新计划基金资助项目(GDYCSZ201482)

Applications of Extrusion Tread Size Control Based on Image Processing

TANG Xunjun   

  1. (School of Electronic Engineering and Automation,Guilin University of Electronic Technology,Guilin 541004,China)
  • Online:2015-07-15 Published:2015-07-13

摘要:

由于目前轮胎胎面挤出机控制系统多以挤出压力反馈控制为主,无法直接反映挤出胎面尺寸,致使一定量挤出胎面尺寸不合格。针对一情况,提出了一种基于图像处理的模糊神经控制方法,利用边缘改进阈值算法分割挤出胎面图像,提取出尺寸数据,数据经由模糊神经网络分析,决策出适宜的挤出机螺杆转速,并反馈给挤出机,仿真实验表明,根据挤出胎面尺寸,模糊神经能较好地进行螺杆转速控制。该控制方法能有效提取挤出胎面尺寸数据,并具有较好的控制效果。

关键词: 挤出胎面, 图像处理, 边缘加强阈值, 模糊神经网络

Abstract:

The tire tread extrusion machine control system is mostly based on extrusion pressure,and the controlling effect cannot directly reflect the extrusion tread size and make it disqualification sometime.In view of this,this paper presents a fuzzy neural network control method based on image processing,using the edge strengthening threshold algorithm to strengthen extrusion tread image and extract the tread data by feedback control based on the fuzzy neural network analysis.The simulation results show that the method has good control over the screw rotation speed,and effectively extracts extrusion tread size data.

Key words: extruded tread;image processing;edge strengthening threshold;fuzzy neural network

中图分类号: 

  • TP391.41