无反复支撑超前支护智能控制系统

韩哲; 徐元强; 张德生; 赵全文; 杜明; 李慧; 周杰; 张帅; 刘杰; 高健勋; 温存宝; 周翔; 赵凯

doi:10.13272/j.issn.1671-251x.2022090004

无反复支撑超前支护智能控制系统

doi: 10.13272/j.issn.1671-251x.2022090004

韩哲^1,,
徐元强²,
张德生¹,
赵全文³,
杜明¹,
李慧⁴,
周杰¹,
张帅¹,
刘杰⁵,
高健勋⁵,
温存宝⁶,
周翔⁷,
赵凯⁸

1.
中煤科工开采研究院有限公司, 北京　100013
2.
华能庆阳煤电有限责任公司, 甘肃庆阳　745002
3.
扎赉诺尔煤业有限责任公司, 内蒙古满洲里　021412
4.
华亭煤业集团有限责任公司, 甘肃华亭　744100
5.
华能煤炭技术研究有限公司, 北京　100070
6.
华能云南滇东能源有限责任公司, 云南曲靖　655000
7.
华能煤业有限公司陕西矿业分公司, 陕西西安　710032
8.
华能煤业有限公司, 北京　100070

基金项目: 国家自然科学基金面上项目（51974159）；国家自然科学基金重点项目（51834006）；山东省重点研发技术项目（2020CXGC011502）；中煤科工开采研究院有限公司“科技创新基金重点项目”（KJ-2021-KCZD-01）；天地科技开采设计事业部“科技创新基金项目”（KJ-2021-KCMS-05）；中国华能总部科技项目（HNKJ20-H48）。

详细信息

作者简介:
韩哲（1989—），男，吉林榆树人，助理研究员，硕士，研究方向为综采工作面智能控制理论与技术，E-mail：343108541@qq.com

中图分类号: TD634
计量
- 文章访问数: 143
- HTML全文浏览量: 108
- PDF下载量: 18
- 被引次数: 0
出版历程
- 收稿日期: 2022-09-02
- 修回日期: 2023-03-28
- 网络出版日期: 2022-11-16

Non-repeated support advanced support intelligent control system

1.
CCTEG Coal Mining Research Institute, Beijing 100013, China
2.
Huaneng Qingyang Coal Power Co., Ltd., Qingyang 745002, China
3.
Zalai Nur Coal Industry Co., Ltd., Manzhouli 021412, China
4.
Huating Coal Mining Group Co., Ltd., Huating 744100, China
5.
Huaneng Coal Technology Research Co., Ltd., Beijing 100070, China
6.
Huaneng Yunnan Diandong Energy Co. , Ltd. , Qujing 655000, China
7.
Shaanxi Mining Branch,Huaneng Coal Industry Co., Ltd., Xi'an 710032,China
8.
Huaneng Coal Industry Co., Ltd.,Beijing 100070, China

摘要

摘要: 针对无反复支撑超前支护装备在空间小、震动大、电磁干扰严重的环境下传感技术水平低、运动控制不精准、作业流程复杂的问题，提出一种无反复支撑超前支护智能控制系统。无反复支撑超前支护工艺的被控需求：具备姿态、障碍物、位置等周边环境信息检测技术手段；具备自适应、自调整、自决策的控制方法；具备快速、平稳、精准的执行部件。根据上述需求，提出智能控制系统的3项关键技术：智能感知、逻辑控制、执行。基于无反复支撑超前支护智能控制系统的控制功能和任务流程，提出了系统总体架构；基于姿态、障碍物识别、压力及位置和速度信息的多传感融合技术手段，提出了多工况运动控制策略。研制了运输巷超前支护“转−运−支”一体样机，并进行地面测试，测试结果表明：无反复支撑超前支护智能控制系统可实现支架中心点及障碍物视觉识别、支架搬运小车自动行走及行程判断、支架自动偏移及旋转、支架自动抓取及升降功能；视觉识别传感器可实现支架架号编码识别、支架姿态、支护区域决策功能；实现了“行—抓—降—转—行—转—升—松—降”自动化作业流程，能够达到应用要求。
- 综采工作面超前支护 /
- 无反复支撑 /
- 智能控制 /
- 多融合感知 /
- 智能感知
Abstract: The non-repeated support advanced support equipment in environments with small space, large vibration, and severe electromagnetic interference has problems of low sensing technology level, imprecise motion control, and complex operation process. In order to solve the above problems, a non-repeated support advanced support intelligent control system is proposed. According to the controlled requirements of the non-repeated support advanced support technology, it has the capability to detect surrounding environmental information such as posture, obstacles, and positions. It has control methods of adaptive, self- adjusting, and self -decision-making. It has fast, stable, and precise execution components. It is pointed out that this intelligent control system proposes three key technologies: intelligent perception, logical control and execution. Based on the control functions and task flow of the intelligent control system for non-repeated support advanced support, the overall architecture of the system is proposed. The multi-sensor fusion technology based on attitude, obstacle recognition, pressure, position, and velocity information is proposed to control and execute multi working condition motion control strategies. The integrated prototype of "turn-transport-support" for advanced support in transportation roadways is developed. And ground tests are conducted. The test results show that the intelligent control system for non-repeated support advanced support can achieve visual recognition of the center point and obstacles of the support, automatic walking and stroke judgment of the support handling trolley, automatic offset and rotation of the support, and automatic grasping and lifting functions of the support. The visual recognition sensor can achieve support frame number coding recognition, support posture, and support area decision-making functions. The automated operation process of "walk-grasp-lower-turn-walk-turn-lift-loose-lower" is implemented. It can meet the application requirements.
- advanced support in fully mechanized working face /
- non-repeated support /
- intelligent control /
- multi fusion perception /
- intelligent perception

HTML全文

图 1 智能控制系统架构

Figure 1. Intelligent control system architecture

下载: 全尺寸图片幻灯片

图 2 系统感知体系

Figure 2. System perception system

下载: 全尺寸图片幻灯片

图 3 系统控制和执行体系

Figure 3. System control and execution system

下载: 全尺寸图片幻灯片

图 4 超前支护“转−运−支”一体样机

Figure 4. Advance support of the "turn-transport-support" prototype

下载: 全尺寸图片幻灯片

图 5 ArUco Marker示例

Figure 5. ArUco Marker demonstration

下载: 全尺寸图片幻灯片

图 6 视觉摄像头及标记物位置

Figure 6. Locations of the visual camera and the markers

下载: 全尺寸图片幻灯片

图 7 基于YOLOv5的顶板区域托盘检测

Figure 7. Top plate area tray detection based on YOLOv5

下载: 全尺寸图片幻灯片

图 8 样机自动控制系统组成

Figure 8. Composition of the prototype automatic control system

下载: 全尺寸图片幻灯片

参考文献(24)

[1]	王国法,赵国瑞,任怀伟. 智慧煤矿与智能化开采关键核心技术分析[J]. 煤炭学报,2019,44(1):34-41. WANG Guofa,ZHAO Guorui,REN Huaiwei. Analysis on key technologies of intelligent coal mine and intelligent mining[J]. Journal of China Coal Society,2019,44(1):34-41.
[2]	王国法,李前,赵志礼,等. 强矿压冲击工作面巷道冲击倾向性测试与超前支护系统研究[J]. 山东科技大学学报(自然科学版),2011,30(4):1-9. WANG Guofa,LI Qian,ZHAO Zhili,et al. The impact tendentiousness testing of working faces and roadways with strong rock burst and fore support system[J]. Journal of Shandong University of Science and Technology(Natural Science),2011,30(4):1-9.
[3]	康红普. 我国煤矿巷道围岩控制技术发展 70 年及展望[J]. 岩石力学与工程学报,2021,40(1):1-30. KANG Hongpu. Seventy years development and prospects of strata control technologies for coal mine roadways in China[J]. Chinese Journal of Rock Mechanics and Engineering,2021,40(1):1-30.
[4]	王国法,庞义辉. 液压支架与围岩耦合关系及应用[J]. 煤炭学报,2015,40(1):30-34. WANG Guofa,PANG Yihui. Relationship between hydraulic support and surrounding rock coupling and its application[J]. Journal of China Coal Society,2015,40(1):30-34.
[5]	王琦,王步康,郑毅. 回采巷道交替循环超前支护技术研究与应用[J]. 采矿与安全工程学报,2022,39(4):750-760. WANG Qi,WANG Bukang,ZHENG Yi. Research and application of alternate circulation advance support technology for mining entry[J]. Journal of Mining & Safety Engineering,2022,39(4):750-760.
[6]	徐亚军,张坤,李丁一,等. 超前支架自适应支护理论与应用[J]. 煤炭学报,2020,45(10):3615-3624. XU Yajun,ZHANG Kun,LI Dingyi,et al. Theory and application of self-adaptive support for advanced powered support[J]. Journal of China Coal Society,2020,45(10):3615-3624.
[7]	李明忠,张德生,刘壮,等. 8.2 m大采高综采工作面超前支护技术研究及应用[J]. 煤炭科学技术,2017,45(11):32-36. LI Mingzhong,ZHANG Desheng,LIU Zhuang,et al. Research and application of advance supporting technology for 8.2 m large mining height fully-mechanized face[J]. Coal Science and Technology,2017,45(11):32-36.
[8]	韩会军,余铜柱. 工作面巷道无反复支撑超前支护研究现状及发展[J]. 矿山机械,2020,48(7):1-4. HAN Huijun,YU Tongzhu. Research status and development of non-repeated advanced support on workface roadway[J]. Mining & Processing Equipment,2020,48(7):1-4.
[9]	刘新华. 采煤工作面沿空巷道无反复支撑超前支护技术[J]. 煤炭工程,2017,49(11):38-40,44. LIU Xinhua. Advance support technology of gob side entry without support in coal mining face[J]. Coal Engineering,2017,49(11):38-40,44.
[10]	张德生,牛艳奇,孟峰. 综采工作面超前支护技术现状及发展[J]. 矿山机械,2014,42(8):1-5. ZHANG Desheng,NIU Yanqi,MENG Feng. Status and development of advance supporting technology on fully mechanized faces[J]. Mining & Processing Equipment,2014,42(8):1-5.
[11]	王国法,任怀伟,赵国瑞,等. 煤矿智能化十大“痛点”解析及对策[J]. 工矿自动化,2021,47(6):1-11. WANG Guofa,REN Huaiwei,ZHAO Guorui,et al. Analysis and countermeasures of ten 'pain points' of intelligent coal mine[J]. Industry and Mine Automation,2021,47(6):1-11.
[12]	闫殿华,周凯,王本林. 迈步分体式超前支护支架的研制与应用[J]. 煤炭科学技术,2014,42(5):81-83,87. YAN Dianhua,ZHOU Kai,WANG Benlin. Development and application of step-separation advanced support[J]. Coal Science and Technology,2014,42(5):81-83,87.
[13]	董华东,李男男. 8 m 大采高临空巷超前支架应用与研究[J]. 煤矿机械,2021,42(4):152-155. DONG Huadong,LI Nannan. Application and research on advance support of 8 m large mining height empty roadway[J]. Coal Mine Machinery,2021,42(4):152-155.
[14]	王莹. 综采工作面垛式超前液压支架设计与应用[J]. 煤矿机械,2021,42(3):160-163. WANG Ying. Design and application of stack advanced hydraulic support in fully mechanized working face[J]. Coal Mine Machinery,2021,42(3):160-163.
[15]	曹风魁,庄严,闫飞,等. 移动机器人长期自主环境适应研究进展和展望[J]. 自动化学报,2020,46(2):205-221. CAO Fengkui,ZHUANG Yan,YAN Fei,et al. Long-term autonomous environment adaptation of mobile robots:state-of-the-art methods and prospects[J]. Acta Automatica Sinica,2020,46(2):205-221.
[16]	王飞跃,魏庆来. 智能控制:从学习控制到平行控制[J]. 控制理论与应用,2018,35(7):939-948. WANG Feiyue,WEI Qinglai. Intelligent control:from learning control to parallel control[J]. Control Theory & Applications,2018,35(7):939-948.
[17]	刘金琨,尔联洁. 多智能体技术应用综述[J]. 控制与决策,2001(2):133-140,180. LIU Jinkun,ER Lianjie. Overview of application of multiagent technology[J]. Control and Decision,2001(2):133-140,180.
[18]	李少远,席裕庚,陈增强,等. 智能控制的新进展(Ⅱ)[J]. 控制与决策,2000(2):136-140. LI Shaoyuan,XI Yugeng,CHEN Zengqiang,et al. The new progresses in intelligent control(Ⅱ)[J]. Control and Decision,2000(2):136-140.
[19]	任怀伟,王国法,赵国瑞,等. 智慧煤矿信息逻辑模型及开采系统决策控制方法[J]. 煤炭学报,2019,44(9):2923-2935. REN Huaiwei,WANG Guofa,ZHAO Guorui,et al. Smart coal mine logic model and decision control method of mining system[J]. Journal of China Coal Society,2019,44(9):2923-2935.
[20]	秦方博,徐德. 机器人操作技能模型综述[J]. 自动化学报,2019,45(8):1401-1418. QIN Fangbo,XU De. Review of robot manipulation skill models[J]. Acta Automatica Sinica,2019,45(8):1401-1418.
[21]	任怀伟,杜毅博,侯刚. 综采工作面液压支架-围岩自适应支护控制方法[J]. 煤炭科学技术,2018,46(1):150-155,191. REN Huaiwei,DU Yibo,HOU Gang. Self adaptive support control method of hydraulic support-surrounding rock in fully-mechanized coal mining face[J]. Coal Science and Technology,2018,46(1):150-155,191.
[22]	杨国威,王以忠,王中任,等. 自主移动焊接机器人嵌入式视觉跟踪控制系统[J]. 计算机集成制造系统,2020,26(11):3049-3056. YANG Guowei,WANG Yizhong,WANG Zhongren,et al. Embedded vision tracking control system for autonomous mobile welding robot[J]. Computer Integrated Manufacturing Systems,2020,26(11):3049-3056.
[23]	李宏刚,王云鹏,廖亚萍,等. 无人驾驶矿用运输车辆感知及控制方法[J]. 北京航空航天大学学报,2019,45(11):2335-2344. LI Honggang,WANG Yunpeng,LIAO Yaping,et al. Perception and control method of driveless mining vehicle[J]. Journal of Beijing University of Aeronautics and Astronautics,2019,45(11):2335-2344.
[24]	杨健健,王超,张强,等. 井工巷道环境建模与掘进障碍检测方法研究[J]. 煤炭科学技术,2020,48(11):12-18. YANG Jianjian,WANG Chao,ZHANG Qiang,et al. Research on environment modeling and excavation obstacle detection method of mine roadway[J]. Coal Science and Technology,2020,48(11):12-18.