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基于掘锚一体机的快速自动铺网技术研究

胡成军, 李杰, 张坤, 潘格格, 马健, 郭刚, 毕经龙, 杜明超

胡成军,李 杰,张 坤,等. 基于掘锚一体机的快速自动铺网技术研究[J]. 煤炭科学技术,2024,52(9):103−111

. DOI: 10.12438/cst.2024-0810
引用本文:

胡成军,李 杰,张 坤,等. 基于掘锚一体机的快速自动铺网技术研究[J]. 煤炭科学技术,2024,52(9):103−111

. DOI: 10.12438/cst.2024-0810

HU Chengjun,LI Jie,ZHANG Kun,et al. Research on fast automatic net-laying technology based on the auxiliary drilling and anchoring integrated machine[J]. Coal Science and Technology,2024,52(9):103−111

. DOI: 10.12438/cst.2024-0810
Citation:

HU Chengjun,LI Jie,ZHANG Kun,et al. Research on fast automatic net-laying technology based on the auxiliary drilling and anchoring integrated machine[J]. Coal Science and Technology,2024,52(9):103−111

. DOI: 10.12438/cst.2024-0810

基于掘锚一体机的快速自动铺网技术研究

基金项目: 

国家自然科学基金资助项目(52104134);第七届中国科协青年人才托举工程资助项目(2021QNRC001);山东省高等学校青创科技支持计划资助项目(2023KG304)

详细信息
    作者简介:

    胡成军: (1986—),男,河南信阳人,高级工程师,博士。E-mail:289926387@qq.com

  • 中图分类号: TD63

Research on fast automatic net-laying technology based on the auxiliary drilling and anchoring integrated machine

Funds: 

National Natural Science Foundation of China (52104134); The 7th China Association for Science and Technology Youth Talent Promotion Project (2021QNRC001); Shandong Provincial Colleges and Universities Youth Innovation Technology Support Project (2023KG304)

More Information
    Author Bio:

    HU Chengjun: 胡成军,男,河南信阳人,高级工程师。中煤天津公司智能矿山研究所副所长,内蒙古自治区煤矿智能化建设工作专家,山西省煤炭学会煤矿智能化委员会副主任委员,山西省“千人智库”专家,中煤基层优秀带头人。研究方向:煤矿智能化掘进技术研究与应用。主要成果:提出智能化掘进工作面的三种建设模式、四个建设阶段,研发了高精度无标定自动定位系统、基于伺服电机控制的多关节自动铺网机器人、矿用自动锚网连扣机、“风尘联动”高效智能除尘系统、掘进智能管控平台等多项成果。承担中国中煤重点科技项目9项,中大型矿井设计近30项,获省部级科技进步一等奖1项、二等奖1项,省部级优秀工程设计咨询奖5项,煤炭行业工程质量奖1项,“五小”创新成果奖4项,授权国家专利20余项,其中发明专利5项,发表论文30余篇

  • 摘要:

    传统铺网作业高度依赖人工,不仅劳动强度大、安全隐患高,而且效率低下,成为制约采掘平衡的重要因素。为实现煤矿井下机器人标准化铺网,通过引入自动化、智能化技术,提升铺网作业效率,减轻工人劳动负荷,增强作业安全性,进而促进煤矿生产的高效、绿色、可持续发展。研究采取了仿真与试验相结合的方法,基于井下特殊环境和作业特点,设计了一种辅助掘锚一体机铺网作业的遥控机械手结构。该结构采用七轴关节型机械臂,搭配顶部抓手,以实现锚网的多角度、高精度铺设。此外,利用先进的计算机仿真技术,对机械臂的动力学性能、运动轨迹规划及受力特点进行分析,通过迭代优化机械臂的结构设计和控制算法,确保其在复杂井下环境中的稳定性和可靠性。同时,针对机械臂的运动控制,开发了一套自适应调整策略,使机械臂能够根据实际工况(如巷道形状、锚网材质等)自动调整运动参数,实现精准、高效的铺网作业。结果表明:自动化铺网设备显著提高了铺网作业的效率,相较于传统人工铺网方式,效率提升超过20%。通过自动化作业,实现了减员33%以上的目标,有效缓解了煤矿井下人力资源紧张的问题。大幅降低了工人的劳动强度,减少了高难度登高作业,降低了工伤风险,劳动强度降低超过80%。同时,自动化铺网过程减少了人为操作失误的可能性,显著提升了作业安全性。未来,随着技术的不断迭代和完善,该技术有望在煤矿智能化建设中发挥更加重要的作用,推动煤矿生产向更加安全、绿色、高效的方向发展。

    Abstract:

    The traditional net-laying operation is highly dependent on manual labor, which not only has high labor intensity and high safety risks, but also has low efficiency, which has become an important factor restricting the balance of mining and excavation. Therefore, the core objective of this study is to design and implement a standardized mesh-laying strategy for underground coal mine robots, which improves the efficiency of mesh-laying operation, reduces the labor load of workers, enhances the safety of operation through the introduction of automation and intelligent technology, and then promotes the efficient, green and sustainable development of coal mine production. In order to realize the above research objectives, this study adopts a combination of simulation and experimental methods, based on the special environment and operating characteristics of underground, and designs a remote-controlled manipulator structure that assists the net-laying operation of digging-anchor integrated machine. The structure adopts a seven-axis articulated robotic arm with a top gripper in order to realize the multi-angle and high-precision laying of anchor nets. In addition, advanced computer simulation technology is used to analyze the dynamic performance, motion trajectory planning and force characteristics of the robotic arm, and the structural design and control algorithm of the robotic arm are optimized iteratively to ensure its stability and reliability in the complex underground environment. At the same time, a set of adaptive adjustment strategy is developed for the motion control of the robotic arm, so that the robotic arm can automatically adjust the motion parameters according to the actual working conditions (tunnel shape, mesh material), and realize accurate and efficient net-laying operation. The results show that the automated net-laying equipment significantly improves the efficiency of net-laying operation, compared with the traditional manual net-laying method, the efficiency is increased by more than 20%. Through automated operation, it realizes the goal of reducing the number of workers by more than 33%, which effectively alleviates the problem of tense human resources in underground coal mines. The labor intensity of workers has been greatly reduced, reducing the high degree of climbing work, reducing the risk of work-related injuries, and the labor intensity has been reduced by more than 80%. At the same time, the automated net-laying process reduces the possibility of human error and significantly improves operational safety. In the future, with the continuous iteration and improvement of the technology, this technology is expected to play a more important role in the intelligent construction of coal mines, and promote the development of coal mine production in the direction of safer, greener and more efficient.

  • 图  1   顶网铺设工况

    Figure  1.   Top net laying condition

    图  2   侧网铺设工况

    Figure  2.   Side net laying condition

    图  3   铺网工艺

    Figure  3.   Netting process

    图  4   锚网结构

    Figure  4.   Anchor net structure

    图  5   自动铺网整体结构

    Figure  5.   Complete structure of automatic net-laying

    图  6   机械手的树状功能

    Figure  6.   Manipulator tree function diagram

    图  7   机械手三维模型

    Figure  7.   Manipulator three-dimensional model

    图  8   抓网机械爪结构

    Figure  8.   Structure of gripper jaws

    图  9   侧网抓取过程

    Figure  9.   Process of grabbing side net

    图  10   空间姿态

    Figure  10.   Spatial attitude

    图  11   求解模型

    Figure  11.   Solving model

    图  12   机械臂等比例仿真模型

    Figure  12.   Robotic arm isometric simulation model

    图  13   机械臂工作范围

    Figure  13.   Working range of robotic arm

    图  14   轨迹参数

    Figure  14.   Trajectory parameters

    图  15   顶网铺设轨迹

    Figure  15.   Top netting trajectory

    图  16   侧网铺设轨迹

    Figure  16.   Side netting trajectory

    图  17   力学模拟

    Figure  17.   Mechanical simulation

    图  18   自动铺网过程

    Figure  18.   Automatic roof mesh laying process

    图  19   网铺设人员构成

    Figure  19.   Composition of net-laying personnel

    表  1   七自由度机械臂D-H参数

    Table  1   Parameters of seven-degree-of-freedom robotic arm D-HTrajectory parameters

    关节iθidi/mmaibi/rad
    1π150π/2
    2π/2025π/2
    3π/200π
    4π2515−π/2
    5π/205−π/2
    6π4000
    70000
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出版历程
  • 收稿日期:  2024-06-17
  • 网络出版日期:  2024-08-22
  • 刊出日期:  2024-09-24

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