燃料粒度检测机器人系统关键技术研究
CSTR:
作者:
作者单位:

作者简介:

曾小信(1982—),男,高级工程师,从事冶金自动化、过程控制、智能检测、机器人应用等方面的研究。

通讯作者:

中图分类号:

TF046.4;TP242

基金项目:

国家重点研发计划课题 (2022YFB3304705)


Research on key technologies of robotic system of fuel grain size measurement
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:

    针对烧结工序燃料粒度无法在线检测,以及人工检测滞后性大的难题,提出了一种基于机器人和多层智能筛分机的燃料粒度检测系统。该系统首先利用取样装置获取燃料样品,再采用微波装置对燃料进行干燥,干燥后的燃料再利用多层智能筛分机进行筛分,最后,利用一体化称重装置获取筛分后的各个粒径的燃料质量,从而计算出燃料粒度分布值。系统在某钢厂投入实际使用,运行结果表明其检测误差<5%,完全可以取代人工检测。重点阐述了该系统涉及的定质量缩分技术、微波快速干燥技术、多层智能筛分技术等关键技术,以期为该系统的改进以及大范围应用提供借鉴与指导。

    Abstract:

    In order to solve the problem that the fuel grain size in the sintering process cannot be detected online and the hysteresis quality of manual detection is large, a fuel grain size measurement system based on robot and multi-layer intelligent screening machine is proposed. The sampling device is used by the system at first to obtain fuel samples, then the microwave device is used to dry the fuel, and the multi-layer intelligent screening machine is used to screen the dried fuel, and finally, the integrated weighing device is used to obtain the fuel quality of each grain size after screening, so as to calculate the fuel grain size distribution value. The system is put into practical use in a steel mill, and the operation results show that its detection error is less than 5%, which could completely replace manual detection. The key technologies involved in the system, such as fixed mass division technology, microwave rapid drying technology and multi-layer intelligent screening technology, are focused on in order to provide reference and guidance for the improvement and large-scale application of the system.

    参考文献
    相似文献
    引证文献
引用本文

曾小信,李宗平,文 武,过宇晟.燃料粒度检测机器人系统关键技术研究[J].烧结球团,2023,48(6):69-74

复制
分享
相关视频

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:2023-08-24
  • 录用日期:
  • 在线发布日期: 2026-09-01
  • 出版日期:
文章二维码