• 论文
主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
基于煤岩可钻性的钻孔机器人自适应控制方法
  • Title

    Adaptive control method for drilling robot based on coal and rock drillability

  • 作者

    李旺年张幼振田宏亮李泉新魏宏超

  • Author

    LI Wangnian;ZHANG Youzhen;TIAN Hongliang;LI Quanxin;WEI Hongchao

  • 单位

    中煤科工西安研究院(集团)有限公司中国地质大学(武汉)自动化学院煤炭科学研究总院有限公司

  • Organization
    CCTEG Xi'an Research Institute (Group) Co., Ltd.
    School of Automation, China University of Geosciences
    CCTEG Chinese Institute of Coal Science
  • 摘要
    由于含煤地层的地质力学环境复杂,导致钻孔机器人给进系统的给进阻力和回转系统的负载转矩复杂多样。现有技术仅通过既定程序控制执行机构进行流程化的动作,钻进过程的自适应智能控制水平低,当钻进工况变化时易造成卡钻、断钻等事故,降低钻孔机器人的钻进效率,影响工作周期。针对该问题,提出一种基于煤岩可钻性的钻孔机器人给进回转双回路PID自适应控制方法。首先以钻进效率和钻进安全为控制目标,选择钻压、转矩作为煤岩可钻性模型的输入参数,运用小波包分解对钻进过程数据进行特征提取,得到样本数据和测试集,利用BP神经网络进行训练和验证,建立煤岩可钻性模型,获取当前钻进工况下推荐钻速和转速。然后基于煤岩可钻性模型,设计了基于PID控制的恒转矩控制策略和恒钻速控制策略,钻孔机器人给进回转控制系统通过恒转矩控制回路对设定钻压进行调整以实现恒转矩控制,通过恒钻速控制回路对设定转矩进行调整以实现恒钻速控制,在确保其安全工作下提高钻进效率。最后建立反映给进回转负载的钻头−煤岩相互作用模型并对钻孔机器人给进回转双回路PID自适应控制方法进行仿真测试。结果表明:① 在煤岩硬度不变时,该控制方法可以实现恒转矩和恒钻速控制,转矩保持在2 000 N·m,钻速保持在6 mm/s。② 在50 s时,增大煤岩硬度,采用自适应调整策略后,钻孔机器人给进回转控制系统的钻压、转速等可以很快达到稳定状态。③ 若推荐钻速6 mm/s对应的实际转矩2 350 N·m超过钻孔机器人工作允许的负载转矩,且其实际转速85 r/min小于推荐转速的95%时,通过钻速微调模块降低推荐钻速设定值,进而通过调整钻压使钻孔机器人的转矩调整至最优转矩,确保钻孔机器人再次稳定在恒转矩和恒钻速控制状态。
  • Abstract
    Due to the complex geological and mechanical environment of coal-bearing strata, the feed resistance of the drilling rig feed system and the load torque of the rotary system are complex and diverse. The existing technology only controls the actuator through established procedures for procedural actions. The adaptive intelligent control level of the drilling process is low. When the drilling conditions change, it is easy to cause accidents such as sticking and breaking. It reduces the drilling efficiency of the drilling robot and affects the work cycle. To solve this problem, a dual loop PID adaptive control method for feed and rotation of drilling robots based on coal rock drillability is proposed. Firstly, with drilling efficiency and drilling safety as control objectives, drilling pressure and torque are selected as input parameters of the coal rock drillability model. Wavelet packet decomposition is used to extract features of drilling process data to obtain sample data and test set. BP neural network is used for training and verification to establish coal rock drillability model and obtain recommended drilling speed and rotation speed under current drilling conditions. Secondly, based on the coal rock drillability model, a constant torque control strategy and a constant drilling speed control strategy based on PID control are designed. The drilling robot feed rotation control system adjusts the set drilling pressure through a constant torque control circuit to achieve constant torque control. The system adjusts the set torque through a constant drilling speed control circuit to achieve constant drilling speed control, improving drilling efficiency while ensuring its safe operation. Finally, A drill-rock interaction model reflecting the feed swing load is developed. The simulation testing is conducted on the dual loop PID adaptive control method for the feed rotation of the drilling robot. The results show the following points. ① When the hardness of coal and rock remains unchanged, this control method can achieve constant torque and constant drilling speed control, with torque maintained at 2 000 N·m and drilling speed maintained at 6 mm/s. ② At 50 seconds, by increasing the hardness of coal and rock and adopting an adaptive adjustment strategy, the drilling robot can quickly reach a stable state in terms of drilling pressure, rotation speed for the rotary control system. ③ If the recommended drilling speed of 6 mm/s corresponds to an actual torque of 2 350 N·m which exceeds the permissible load torque for the operation of the drilling robot and the actual speed of 85 r/min is less than 95% of the recommended speed, the recommended drilling speed setting is reduced by means of the drilling speed trim module. The drilling pressure is adjusted to adjust the drilling robot's torque to the optimal torque, ensuring that the drilling robot is stable again in the constant torque and constant drilling speed control state.
  • 关键词

    智能化钻探钻孔机器人煤岩可钻性钻进效率钻进安全PID自适应控制

  • KeyWords

    intelligent drilling;drilling robot;coal rock drillability;drilling efficiency;drilling safety;PID adaptive control

  • 基金项目(Foundation)
    陕西省自然科学基础研究计划项目(2023-JC-YB-341);天地科技股份有限公司科技创新创业资金专项项目(2022-2-TD-ZD006);中煤科工集团西安研究院有限公司科技创新基金项目(2020XAYDC01-03)。
  • 文章目录
    0 引言
    1 钻孔机器人给进回转自适应控制系统
    1.1 钻孔机器人状态智能感知
    1.2 钻孔机器人智能控制中心
    2 基于煤岩可钻性的给进回转模型
    2.1 煤岩可钻性建模
    2.2 确定推荐钻速和转速
    3 钻孔机器人给进回转系统自适应控制策略
    3.1 基于PID控制的恒转矩控制策略
    3.2 基于PID控制的恒钻速控制策略
    4 仿真测试
    4.1 给进回转负载仿真模型建立
    4.2 仿真效果分析
    5 结论
  • DOI
  • 引用格式
    李旺年,张幼振,田宏亮,等. 基于煤岩可钻性的钻孔机器人自适应控制方法[J]. 工矿自动化,2023,49(6):182-188.
  • Citation
    LI Wangnian, ZHANG Youzhen, TIAN Hongliang, et al. Adaptive control method for drilling robot based on coal and rock drillability[J]. Journal of Mine Automation,2023,49(6):182-188.
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