滚筒采煤机智能变速截割控制研究
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  • 英文篇名:Research on Intelligent Variable Speed Cutting Control of Drum Shearer
  • 作者:牛瑞军
  • 英文作者:NIU Rui-jun;Shanxi Xishan Jinxing Energy Co.,Ltd;
  • 关键词:采煤机 ; 智能化 ; 变速截割 ; 仿真模型
  • 英文关键词:shearer;;intelligent;;variable speed cutting;;simulation model
  • 中文刊名:JXYJ
  • 英文刊名:Mechanical Research & Application
  • 机构:山西西山晋兴能源有限责任公司;
  • 出版日期:2019-06-28
  • 出版单位:机械研究与应用
  • 年:2019
  • 期:v.32;No.161
  • 语种:中文;
  • 页:JXYJ201903065
  • 页数:4
  • CN:03
  • ISSN:62-1066/TH
  • 分类号:210-213
摘要
以斜沟矿300 k W电牵引滚筒采煤机为研究对象,通过对采煤机截割煤壁时运动学分析,推导出牵引速度和滚筒转速相关的运动力学方程式,基于此运用Matlab/Simulink工具建立采煤机仿真模型,分析煤层截割阻抗与电牵引滚筒采煤机截割电机定子电流的关系,进而提出煤壁截割阻抗的识别方法和采煤机智能变速截割控制方法。采煤机仿真模型运用该方法后进行截割煤壁作业,从煤壁截割过程可以看出,智能变速截割调速控制方法效果十分明显,采煤机能够有效识别煤层截割阻抗,进行自动、智能化变速截割作业。
        In this paper,the 300 k W electric traction drum shearer in the inclined trench mine is taken as the research object.Through the kinematics analysis of the shearer cutting the coal wall,the motion mechanics equation related to the traction speed and drum speed is derived. Based on this,the simulation model of shearer is established by using the Matlab/Simulink tool,and the relationship between the coal seam cutting impedance and the stator current of the electric traction drum shearer cutting motor is analyzed; then the identification method of coal wall cutting impedance and the intelligent variable speed cutting control method of shearer are proposed. After using this method in the simulation model of shearer,it can be seen from the coal wall cutting process that the intelligent variable speed cutting speed control method is very effective,and the shearer can effectively identify the cutting impedance of coal seam and carry out automatic,intelligent variable speed cutting operation.
引文
[1]柳君波,高俊莲,徐向阳.中国煤炭供应行业格局优化及排放[J].自然资源学报,2019,34(3):473-486.
    [2]常江,姬智,张心伦.我国近现代煤炭资源型城市发展、问题及趋势初探[J].资源与产业,2019(4):1-9.
    [3]刘晓敏.基于PLC控制的采煤机自动割煤技术浅析[J].当代化工研究,2019(4):96-97.
    [4]耿洁.采煤机高效截割的自适应调速研究[D].北京:中国矿业大学,2017.
    [5]闫忠.采煤机自适应变速截割控制研究[D].重庆:重庆大学,2016.
    [6]潘健.采煤机端头记忆截割关键技术研究[D].北京:中国矿业大学,2016.

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