煤炭工程 ›› 2024, Vol. 56 ›› Issue (3): 84-90.doi: 10.11799/ce202403013

• 生产技术 • 上一篇    下一篇

综掘巷道迈步式自移机尾智能控制技术研究

董志超,代鹰,王蒙,等   

  1. 1. 国家能源集团神东煤炭分公司哈拉沟煤矿
    2. 山东鸿灿机电设备股份有限公司
  • 收稿日期:2023-09-24 修回日期:2023-11-11 出版日期:2024-03-20 发布日期:2024-03-25
  • 通讯作者: 董志超 E-mail:dzc3177@126.com

Research on Intelligent Control Technology of step-by-step self-moving tail in fully Mechanized roadway

  • Received:2023-09-24 Revised:2023-11-11 Online:2024-03-20 Published:2024-03-25

摘要: 针对现有综掘巷道迈步式自移机尾设备智能化水平低, 智能控制技术研究不足等问题, 阐释了自移机尾工作原理, 分析了智能化煤矿验收办法中针对带式输送机自移机尾智能化的要求, 提出自移机尾控制系统的总体设计方案, 设计了一键自移控制、多机联动控制和人员接近识别与闯入预警软硬件系统。在此基础上, 在神华集团神东煤炭有限责任公司哈拉沟煤矿31107 运输巷掘进工作面自移机尾应用该智能控制系统, 现场试验结果表明: 该智能控制系统可实现自移机尾的一键自移控制; 人员接近识别与闯入预警系统可以对自移机尾周边人员进行精准定位, 并且能够在人员进入危险区域后进行识别, 提高了自移机尾设备使用的安全性。

关键词: 掘进工作面, 自移机尾, 带式输送机, 智能控制

Abstract: Considering the low intelligence level of the existing step-by-step self-moving tail equipment in fully mechanized roadway and the lack of research on intelligent control technology, the intelligent control technology is studied. According to the structural characteristics, working principle and working conditions of the self-moving machine tail and the requirements put forward by the intelligent coal mine acceptance method issued by the state for the intelligent tail of the belt conveyor, this paper puts forward the overall design scheme of the self-moving machine tail control system. The software and hardware systems are designed for one-button self-shift control technology, multi-machine linkage control technology and personnel approach identification and intrusion early warning technology. The intelligent control technology of self-moving tail studied in this paper is applied to the heading face of 31107 transportation trough in Halagou Coal Mine of Shenhua Group Shendong Coal Co., Ltd., and more than 1000 meters of driving operation is successfully applied, and the field use is good. The intelligent control of self-moving tail can be realized. The personnel approach identification and intrusion early warning technology studied in this paper can accurately locate the people around the tail of the self-moving machine, and the posi-tioning error is less than 30cm, and can identify the personnel after entering the dangerous area, which improves the safety of the self-moving tail equipment. The research results of this paper can provide support for the in-telligent construction of underground heading face in coal mine.

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