基于机器视觉的磨粉机轧距监测系统研究
CSTR:
作者:
作者单位:

作者简介:

吕少杰,男,河南工业大学在读硕士研究生

通讯作者:

中图分类号:

基金项目:

河南省重点研发与推广项目(编号:2018304)


Research on mill distance monitoring system based on machine vision
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:

    目的:实现磨粉机磨辊轧距的实时监测。方法:采用CCD工业相机采集轧距图片,利用阈值分割、形态学方法对采集的灰度图像进行预处理操作,再利用边缘检测算法并结合MATLAB软件和数学运算剔除边缘无关点,最终计算出磨粉机的轧距。通过比较塞尺测量轧距值与系统监测值,验证系统的可行性和准确性。结果:稳定状态下该在线监测系统的数据波动幅度为0.001~0.002 mm,增速状态下波动幅度较大,为0.001~0.005 mm。结论:该系统可实时测量磨辊轧距。

    Abstract:

    Objective: Real-time monitoring of the grinding roller distance of the pulverizer. Methods: CCD industrial camera was used to collect the rolling distance image, threshold segmentation and morphology were used to preprocess the gray image, and then the edge detection algorithm combined with MATLAB software and mathematical operation were used to eliminate the irrelevant edge points, and finally the rolling distance of the mill was calculated. The feasibility and veracity of the system were verified by comparing the value of gauge and the value of system monitoring. Results: The data fluctuation range of the online monitoring system was 0.001~0.002 mm in the steady state, and the fluctuation range was larger in the speeding state, which was 0.001~0.005 mm. Conclusion: The system can measure rolling distance in real time.

    参考文献
    相似文献
    引证文献
引用本文

吕少杰,武文斌,张文龙,等.基于机器视觉的磨粉机轧距监测系统研究[J].食品与机械,2022,(11):101-104,110.
LU Shao-jie, WU Wen-bin, ZHANG Wen-long, et al. Research on mill distance monitoring system based on machine vision[J]. Food & Machinery,2022,(11):101-104,110.

复制
相关视频

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: 2022-12-15
  • 出版日期:
文章二维码
×
《食品与机械》
友情提示
友情提示 一、 近日有不少作者反应我刊官网无法打开,是因为我刊网站正在升级,旧网站仍在百度搜索排名前列。请认准《食品与机械》唯一官方网址:http://www.ifoodmm.com/spyjx/home 唯一官方邮箱:foodmm@ifoodmm.com; 联系电话:0731-85258200,希望广大读者和作者仔细甄别。