东北大学学报:自然科学版 ›› 2014, Vol. 35 ›› Issue (7): 974-977.DOI: 10.12068/j.issn.1005-3026.2014.07.014

• 材料与冶金 • 上一篇    下一篇

基于机器视觉的薄带铸轧熔池液位识别方法

李家栋,王昭东,曹光明,王国栋   

  1. (东北大学 轧制技术及连轧自动化国家重点实验室, 辽宁 沈阳110819)
  • 收稿日期:2013-10-08 修回日期:2013-10-08 出版日期:2014-07-15 发布日期:2014-04-11
  • 通讯作者: 李家栋
  • 作者简介:李家栋(1983-),男,辽宁营口人,东北大学博士后研究人员;王昭东(1968-),男,安徽淮南人,东北大学教授,博士生导师;王国栋(1942-),男,辽宁大连人,东北大学教授,博士生导师,中国工程院院士.
  • 基金资助:
    国家科技支撑计划项目(2012BAE03B02);东北大学博士后基金资助项目

Recognition Method of the Molten Steel Level in the Strip Casting Process Based on the Machine Vision

LI Jiadong, WANG Zhaodong, CAO Guangming, WANG Guodong   

  1. State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819, China.
  • Received:2013-10-08 Revised:2013-10-08 Online:2014-07-15 Published:2014-04-11
  • Contact: LI Jiadong
  • About author:-
  • Supported by:
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摘要: 为解决薄带铸轧熔池液位难检测的问题,研发机器视觉识别熔池钢水液位的方法.利用线阵CCD下熔池钢水与铸轧辊灰度值有明显差别的图像特征,建立熔池液位的机器视觉检测系统.利用所选线阵相机采集图像速度快的特性,提出基于时间建立熔池液位图像原型的方法,建立了以滤波处理、二值化处理和边界识别为核心的熔池液位视觉识别模型.使用建立的系统和模型在实验室铸轧机和感应加热炉上进行了测试实验,结果表明:所建的熔池液位视觉检测系统和识别方法具备可行性,具有较高的检测精度和较快的检测速度,能够满足工业生产需要.

关键词: 熔池液位, CCD相机, 图像处理, 边缘识别, 双辊铸轧

Abstract: A recognition method based on the machine vision was designed and investigated to solve the problem on the measurement of molten steel level in the strip casting processing. Based on the different image grey values captured by linear CCD camera between the molten steel and casting rolls, a machine vision system for measuring molten steel level was designed. By the high speed character of the linear camera image data acquisition, a method to create molten steel level original image by the time was proposed and the molten steel level recognition model was established building with filtering, binarization and boundary recognition as the core. The system and model were tested on a smallscale strip casting machine and the induction furnace respectively. The results illustrate that the molten steel level detection system and its recognition method are feasible, which show high levels of the precision and response speed and can be applied in the industrial line for the strip casting.

Key words: molten steel level, CCD camera, image treatment, edge recognition, twinroll strip casting

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