基于煤岩可钻性的钻孔机器人自适应控制方法

李旺年; 张幼振; 田宏亮; 李泉新; 魏宏超

doi:10.13272/j.issn.1671-251x.2022110047

基于煤岩可钻性的钻孔机器人自适应控制方法

doi: 10.13272/j.issn.1671-251x.2022110047

李旺年^{1, 2},
张幼振^{1, 3},
田宏亮^{1, 3},
李泉新^{1, 3},
魏宏超^{1, 3}

1.
中煤科工西安研究院(集团)有限公司, 陕西西安　710077
2.
中国地质大学(武汉) 自动化学院, 湖北武汉　430074
3.
煤炭科学研究总院有限公司, 北京　100013

基金项目: 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）。

详细信息

作者简介:
李旺年（1987—），男，陕西吴堡人，在读博士研究生，副研究员，从事煤矿井下钻探技术与装备研发工作，E-mail：liwangniancctegxian.com

中图分类号: TD77
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出版历程
- 收稿日期: 2022-11-12
- 修回日期: 2023-06-25
- 网络出版日期: 2023-06-30

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

LI Wangnian^{1, 2},
ZHANG Youzhen^{1, 3},
TIAN Hongliang^{1, 3},
LI Quanxin^{1, 3},
WEI Hongchao^{1, 3}

1.
CCTEG Xi'an Research Institute (Group) Co., Ltd., Xi'an 710077, China
2.
School of Automation, China University of Geosciences, Wuhan 430074, China
3.
CCTEG Chinese Institute of Coal Science, Beijing 100013, China

摘要

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。
- 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
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.
- intelligent drilling /
- drilling robot /
- coal rock drillability /
- drilling efficiency /
- drilling safety /
- PID adaptive control

HTML全文

图 1 钻孔机器人给进回转自适应控制系统

Figure 1. Drilling robot feed and rotary adaptive control system

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图 2 给进回转自适应控制系统结构

Figure 2. Structure of feed and rotary adaptive control system

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图 3 设定钻速调整下的转矩变化

Figure 3. Torque change under set drilling speed adjustment

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图 4 设定钻速调整下的钻速变化

Figure 4. Drilling speed change under set drilling speed adjustment

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图 5 设定钻速调整下的转速变化

Figure 5. Rotational speed change under set drilling speed adjustment

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图 6 设定钻速调整下的钻压变化

Figure 6. Drilling pressure change under set drilling speed adjustment

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图 7 设定钻速调整下的给进力变化

Figure 7. Feed force change under set drilling speed adjustment

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参考文献(22)

[1]	石智军,李泉新,姚克. 煤矿井下智能化定向钻探发展路径与关键技术分析[J]. 煤炭学报,2020,45(6):2217-2224. SHI Zhijun,LI Quanxin,YAO Ke. Development path and key technology analysis of intelligent directional drilling in underground coal mine[J]. Journal of China Coal Society,2020,45(6):2217-2224.
[2]	葛世荣,胡而已,裴文良. 煤矿机器人体系及关键技术[J]. 煤炭学报,2020,45(1):455-463. GE Shirong,HU Eryi,PEI Wenliang. Classification system and key technology of coal mine robot[J]. Journal of China Coal Society,2020,45(1):455-463.
[3]	柴天佑, 岳恒. 自适应控制[M]. 北京: 清华大学出版社, 2016. CHAI Tianyou, YUE Heng. Adaptive control[M]. Beijing: Tsinghua University Press, 2016.
[4]	张幼振,范涛,阚志涛,等. 煤矿巷道掘进超前钻探技术应用与发展[J]. 煤田地质与勘探,2021,49(5):286-293. ZHANG Youzhen,FAN Tao,KAN Zhitao,et al. Application and development of advanced drilling technology for coal mine roadway heading[J]. Coal Geology & Exploration,2021,49(5):286-293.
[5]	李泉新,刘飞,方俊. 煤矿坑道智能化钻探技术发展框架分析[J]. 工矿自动化,2020,46(10):9-13,25. LI Quanxin,LIU Fei,FANG Jun. Analysis of development framework of intelligent coal mine underground drilling technology[J]. Industry and Mine Automation,2020,46(10):9-13,25.
[6]	LIAO Xiufeng,KHANDELWAL M,YANG Haiqing,et al. Effects of a proper feature selection on prediction and optimization of drilling rate using intelligent techniques[J]. Engineering with Computers,2020,36(2):499-510. doi: 10.1007/s00366-019-00711-6
[7]	翁寅生,姚克,殷新胜. 坑道钻机参数测量系统及其在煤矿中的应用[J]. 煤矿安全,2016,47(11):117-119,123. WENG Yinsheng,YAO Ke,YIN Xinsheng. Application of parameter measuring system of tunnel drilling rig in coal mine[J]. Safety in Coal Mines,2016,47(11):117-119,123.
[8]	马斌,董洪波. 煤矿井下坑道钻机电液控制系统的设计[J]. 煤矿机械,2021,42(1):13-15. MA Bin,DONG Hongbo. Design of electro-hydraulic control system for underground coal mine tunnel drilling rig[J]. Coal Mine Machinery,2021,42(1):13-15.
[9]	王清峰,陈航,周涛. 煤矿井下自动化钻进技术及装备的发展历程与展望[J]. 矿业安全与环保,2022,49(4):45-50. WANG Qingfeng,CHEN Hang,ZHOU Tao. Development history and prospect of automatic drilling technology and equipment in coal mine[J]. Mining Safety & Environmental Protection,2022,49(4):45-50.
[10]	王清峰,陈航,陈玉涛. 钻孔机器人钻进工况智能感知与自适应控制机理研究[J]. 矿业安全与环保,2021,48(3):1-5. WANG Qingfeng,CHEN Hang,CHEN Yutao. Research on the mechanism of intelligent sensing and adaptive control in drilling condition of drilling robot[J]. Mining Safety & Environmental Protection,2021,48(3):1-5.
[11]	董洪波,姚宁平,马斌,等. 煤矿井下坑道钻机电控自动化技术研究[J]. 煤田地质与勘探,2020,48(3):219-224. DONG Hongbo,YAO Ningping,MA Bin,et al. Research on electronically controlled automation technology of underground drilling rig for coal mine[J]. Coal Geology & Exploration,2020,48(3):219-224.
[12]	张锐,姚克,方鹏,等. 煤矿井下自动化钻机研发关键技术[J]. 煤炭科学技术,2019,47(5):59-63. ZHANG Rui,YAO Ke,FANG Peng,et al. Key technologies for research and development of automatic drilling rig in underground coal mine[J]. Coal Science and Technology,2019,47(5):59-63.
[13]	张幼振,张宁,邵俊杰,等. 基于钻进参数聚类的含煤地层岩性模糊识别[J]. 煤炭学报,2019,44(8):2328-2335. ZHANG Youzhen,ZHANG Ning,SHAO Junjie,et al. Fuzzy identification of coal-bearing strata lithology based on drilling parameter clustering[J]. Journal of China Coal Society,2019,44(8):2328-2335.
[14]	谢志江,常雪,杨林,等. 基于机械比能理论的煤岩可钻性分级方法[J]. 煤田地质与勘探,2021,49(3):236-243. doi: 10.3969/j.issn.1001-1986.2021.03.030 XIE Zhijiang,CHANG Xue,YANG Lin,et al. Classification method of coal and rock drillability based on mechanical specific energy theory[J]. Coal Geology & Exploration,2021,49(3):236-243. doi: 10.3969/j.issn.1001-1986.2021.03.030
[15]	方鹏. 煤矿坑道定向钻机钻进参数监测系统设计[J]. 工矿自动化2019, 45（1）: 1-5. FANG Peng. Design of drilling parameters monitoring system of directional drilling rig in coal mine tunnel[J]. Industry and Mine Automation, 2019, 45（1）: 1-5.
[16]	吴敏, 曹卫华, 陈鑫, 等. 复杂地质钻进过程智能控制[M]. 北京: 科学出版社, 2022. WU Min, CAO Weihua, CHEN Xin, et al. Intelligent control of the complex geological drilling process[M]. Beijing: Science Press, 2022.
[17]	GAN Chao,CAO Weihua,LIU Kangzhi,et al. A novel dynamic model for the online prediction of rate of penetration and its industrial application to a drilling process[J]. Journal of Process Control,2022,109:83-92. doi: 10.1016/j.jprocont.2021.12.002
[18]	苏义脑. 井下控制工程学概述及其研究进展[J]. 石油勘探与开发,2018,45(4):754-763. doi: 10.11698/PED.2018.04.16 SU Yi'nao. Introduction to the theory and technology on downhole control engineering and its research progress[J]. Petroleum Exploration and Development,2018,45(4):754-763. doi: 10.11698/PED.2018.04.16
[19]	胡业林,代斌,宋晓. 基于小波包和AFSA−SVM的电机故障诊断[J]. 电子测量技术,2021,44(2):48-55. doi: 10.19651/j.cnki.emt.2005463 HU Yelin,DAI Bin,SONG Xiao. Motor fault diagnosis based on wavelet packet and AFSA-SVM[J]. Electronic Measurement Technology,2021,44(2):48-55. doi: 10.19651/j.cnki.emt.2005463
[20]	GUO Yinan,CHENG Wei,GONG Dunwei,et al. Adaptively robust rotary speed control of an anchor-hole driller under varied surrounding rock environments[J]. Control Engineering Practice,2019,86:24-36. doi: 10.1016/j.conengprac.2019.02.002
[21]	MA S, WU Min, CHEN Luefeng, et al. Robust mixed-sensitivity H∞ control of weight on bit in geological drilling process with parameter uncertainty[J]. Journal of the Franklin Institute, 2021（17）.
[22]	NAVARRO-LOPEZ E M, CORTES D. Sliding-mode control of a multi-dof oilwell drillstring with stick-slip oscillations[C]. Proceedings of the 2007 American Control Conference, New York, 2007: 3837-3842.