液压支架姿态数字孪生精准快速映射方法

刘萌; 付翔; 姜玉龙; 刘彬; 杨宇琪; 秦一凡; 孙岩

doi:10.13272/j.issn.1671-251x.18180

液压支架姿态数字孪生精准快速映射方法

doi: 10.13272/j.issn.1671-251x.18180

刘萌^1,,
付翔^{1, 2, 3},
姜玉龙^{1, 2, 4, ,},
刘彬¹,
杨宇琪¹,
秦一凡¹,
孙岩¹

1.
太原理工大学矿业工程学院，山西太原　030024
2.
山西焦煤集团有限责任公司博士后工作站，山西太原　030024
3.
太原理工大学智能采矿装备技术全国重点实验室，山西太原　030024
4.
太原理工大学原位改性采矿教育部重点实验室，山西太原　030024

基金项目: 国家自然科学基金项目（52274157）；“科技兴蒙”行动重点专项项目（2022EEDSKJXM010）。

详细信息

作者简介:
刘萌（1997—），男，山东菏泽人，硕士研究生，研究方向为智慧煤矿工业互联网技术，E-mail：419549475@qq.com

通讯作者:
姜玉龙（1990—），男，吉林松原人，讲师，博士，主要研究方向为矿山压力与岩层控制、智能化开采及煤层气开采，E-mail：13485368423@163.com。

中图分类号: TD355
计量
- 文章访问数: 96
- HTML全文浏览量: 26
- PDF下载量: 13
- 被引次数: 0
出版历程
- 收稿日期: 2024-02-02
- 修回日期: 2024-06-26
- 网络出版日期: 2024-07-04

Precise and fast digital twin mapping method for hydraulic support attitude

LIU Meng^1
,,
FU Xiang^{1, 2, 3},
JIANG Yulong^{1, 2, 4
, ,},
LIU Bin¹,
YANG Yuqi¹,
QIN Yifan¹,
SUN Yan¹

1.
College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
2.
Post-doctoral Workstation, Shanxi Coking Coal Group Co., Ltd., Taiyuan 030024, China
3.
State Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan University of Technology, Taiyuan 030024, China
4.
Key Laboratory of In-Situ Property-Improving Mining of Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China

摘要

摘要: 针对应用数字孪生实现综采工作面液压支架姿态映射存在精度低、时延大及精度与时延难以平衡等问题，提出了一种液压支架姿态数字孪生精准快速映射方法。设计了包括物理感知层、数据层、业务逻辑层和表现层的液压支架姿态数字孪生系统架构；在业务逻辑层，通过保留液压支架高精度模型外部形状并将关键部位合并成轻量化结构件，建立了液压支架姿态数字孪生模型，减少了渲染时延，并通过建立倾角传感器测量角度与数字孪生模型转动角度之间的转换关系，实现液压支架姿态数字孪生模型与液压支架实体虚实映射一致，保证了液压支架姿态映射的精度；在数据层，从各数据传输环节中划分出传输间隔并进行参数约束，应用参数规划求解优化可调环节的数据更新间隔，减少了数字孪生系统数据传输过程的资源浪费和时延。搭建了液压支架姿态数字孪生精准快速映射平台，进行液压支架姿态虚实映射的时延和精度测试，结果表明，该方法在保证液压支架姿态映射精度的前提下具有较低的时延。
- 液压支架 /
- 数字孪生 /
- 虚实映射 /
- 渲染时延 /
- 数据传输时延 /
- 参数规划求解
Abstract: A precise and fast digital twin mapping method for hydraulic support attitude in fully mechanized working face is proposed to address the problems of low precision, large time delay, and difficulty in balancing precision and time delay in implementing attitude mapping using digital twins. The study designs a digital twin system architecture for hydraulic support attitude, which includes physical perception layer, data layer, business logic layer, and presentation layer. At the business logic layer, by retaining the external shape of the high-precision model of the hydraulic support and merging key parts into lightweight structural components, a digital twin model of the hydraulic support attitude is established. It reduces rendering delay. By establishing a conversion relationship between the angle measured by the inclination sensor and the rotation angle of the digital twin model, consistent of virtual-real mapping of the digital twin model of the hydraulic support attitude and real entities of the hydraulic support is achieved, ensuring the precision of the hydraulic support attitude mapping. At the data layer, transmission intervals are divided from each data transmission link and parameter constraints are applied. Parameter programming is applied to optimize the data update interval of adjustable links, reducing resource waste and latency in the data transmission process of digital twin systems. A precise and fast digital twin mapping platform for hydraulic support attitude is built, and the time delay and precision of virtual real mapping for hydraulic support attitude are tested. The results show that this method has a lower time delay while ensuring the precision of hydraulic support attitude mapping.
- hydraulic support /
- digital twin /
- virtual real mapping /
- rendering latency /
- data transmission delay /
- parameter planning solution

HTML全文

图 1 液压支架姿态数字孪生系统架构

Figure 1. Hydraulic support attitude digital twin system architecture

下载: 全尺寸图片幻灯片

图 2 液压支架倾角传感器安装位置

Figure 2. Hydraulic support tilt sensor installation position

下载: 全尺寸图片幻灯片

图 3 液压支架数字孪生模型简化结构

Figure 3. Simplified structure of hydraulic support digital twin model

下载: 全尺寸图片幻灯片

图 4 液压支架数字孪生精准快速映射平台

Figure 4. Hydraulic support digital twin precise and fast mapping platform

下载: 全尺寸图片幻灯片

图 5 模型映射时延测试结果

Figure 5. Model mapping delay test results

下载: 全尺寸图片幻灯片

图 6 液压支架姿态平均绝对误差结果

Figure 6. Mean absolute error result of hydraulic support attitude

下载: 全尺寸图片幻灯片

参考文献(21)

[1]	魏文艳. 综采工作面智能化开采技术发展现状及展望[J]. 煤炭科学技术,2022,50(增刊2):244-253. WEI Wenyan. Development status and prospect of intelligent mining technology of longwall mining[J]. Coal Science and Technology,2022,50(S2):244-253.
[2]	金智新,闫志蕊,王宏伟,等. 新一代信息技术赋能煤矿装备数智化转型升级[J]. 工矿自动化,2023,49(6):19-31. JIN Zhixin,YAN Zhirui,WANG Hongwei,et al. The new generation of information technology empowers the digital and intelligent transformation and upgrading of coal mining equipment[J]. Journal of Mine Automation,2023,49(6):19-31.
[3]	丁恩杰,俞啸,夏冰,等. 矿山信息化发展及以数字孪生为核心的智慧矿山关键技术[J]. 煤炭学报,2022,47(1):564-578. DING Enjie,YU Xiao,XIA Bing,et al. Development of mine informatization and key technologies of intelligent mines[J]. Journal of China Coal Society,2022,47(1):564-578.
[4]	张帆,李闯,李昊,等. 面向智能矿山与新工科的数字孪生技术研究[J]. 工矿自动化,2020,46(5):15-20. ZHANG Fan,LI Chuang,LI Hao,et al. Research on digital twin technology for smart mine and new engineering discipline[J]. Industry and Mine Automation,2020,46(5):15-20.
[5]	张帆,葛世荣. 矿山数字孪生构建方法与演化机理[J]. 煤炭学报,2023,48(1):510-522. ZHANG Fan,GE Shirong. Construction method and evolution mechanism of mine digital twins[J]. Journal of China Coal Society,2023,48(1):510-522.
[6]	张帆,葛世荣,李闯. 智慧矿山数字孪生技术研究综述[J]. 煤炭科学技术,2020,48(7):168-176. ZHANG Fan,GE Shirong,LI Chuang. Research summary on digital twin technology for smart mines[J]. Coal Science and Technology,2020,48(7):168-176.
[7]	苗丙,葛世荣,郭一楠,等. 煤矿数字孪生智采工作面系统构建[J]. 矿业科学学报,2022,7(2):143-153. MIAO Bing,GE Shirong,GUO Yinan,et al. Construction of digital twin system for intelligent mining in coal mines[J]. Journal of Mining Science and Technology,2022,7(2):143-153.
[8]	葛世荣,王世博,管增伦,等. 数字孪生——应对智能化综采工作面技术挑战[J]. 工矿自动化,2022,48(7):1-12. GE Shirong,WANG Shibo,GUAN Zenglun,et al. Digital twin:meeting the technical challenges of intelligent fully mechanized working face[J]. Journal of Mine Automation,2022,48(7):1-12.
[9]	林承志,黄华,张仕祥. 基于Unity的制造业自动化生产线数字孪生平台设计[J]. 唐山学院学报,2023,36(3):38-43,84. LIN Chengzhi,HUANG Hua,ZHANG Shixiang. Design of digital twin platform for automated production line based on Unity[J]. Journal of Tangshan University,2023,36(3):38-43,84.
[10]	李阿乐,郑晓雯,辛海林,等. 基于Unity 3D的液压支架运动仿真系统研究[J]. 机电产品开发与创新,2014,27(5):79-81. LI Ale,ZHENG Xiaowen,XIN Hailin,et al. Research on motion simulation system of hydraulic support based on Unity 3D[J]. Development & Innovation of Machinery & Electrical Products,2014,27(5):79-81.
[11]	刘清,张龙,李天越,等. 综采工作面三机数字孪生及协同建模方法[J]. 工矿自动化,2023,49(2):47-55. LIU Qing,ZHANG Long,LI Tianyue,et al. A three machine digital twin and collaborative modeling method for fully mechanized working face[J]. Journal of Mine Automation,2023,49(2):47-55.
[12]	柳林燕,杜宏祥. 工业机器人数字孪生实时作业控制、监控与精度补偿方法:CN109571476A[P]. 2019-04-05. LIU Linyan,DU Hongxiang. Real-time operation control,monitoring,and accuracy compensation method for industrial robot digital twin:CN109571476A[P]. 2019-04-05.
[13]	康瑞浩,胡俊山,田威,等. 面向工业机器人的数字孪生建模精度补偿方法[J]. 航空制造技术,2023,66(6):50-59. KANG Ruihao,HU Junshan,TIAN Wei,et al. A digital twin modelling accuracy compensation method for industrial robots[J]. Aeronautical Manufacturing Technology,2023,66(6):50-59.
[14]	洪飞. 基于数字孪生和数据驱动的新型煤矿智能支护监控系统设计[J]. 煤矿现代化,2021,30(5):116-118,122. doi: 10.3969/j.issn.1009-0797.2021.05.038 HONG Fei. Design of novel coal mine intelligent support monitoring system based on digital twin and data driven[J]. Coal Mine Modernization,2021,30(5):116-118,122. doi: 10.3969/j.issn.1009-0797.2021.05.038
[15]	王宏伟,武亚丹,陈龙. 液压支架数字孪生体联合建模方法[J]. 工矿自动化,2022,48(10):13-19. WANG Hongwei,WU Yadan,CHEN Long. Hydraulic support digital twin joint modeling method[J]. Journal of Mine Automation,2022,48(10):13-19.
[16]	朱海峰,陈晓,房雨雨,等. 面向数字孪生的三维室内场景快速高精度重建方法及系统:CN115512040A[P]. 2022-12-23. ZHU Haifeng,CHEN Xiao,FANG Yuyu,et al. Rapid and high-precision reconstruction method and system for three-dimensional indoor scenes oriented to digital twin:CN115512040A[P]. 2022-12-23.
[17]	李梅,姜展,满旺,等. 基于虚幻引擎的智能矿山数字孪生系统云渲染技术[J]. 测绘通报,2023(1):26-30. LI Mei,JIANG Zhan,MAN Wang,et al. Study on could rendering technology of intelligent mine digital twin system using unreal engine[J]. Bulletin of Surveying and Mapping,2023(1):26-30.
[18]	崔耀,李天越,叶壮,等. 综采跟机工艺数字孪生系统架构与关键技术[J]. 工矿自动化,2023,49(2):56-62,76. CUI Yao,LI Tianyue,YE Zhuang,et al. Digital twin system architecture and key technology of following process for fully mechanized mining[J]. Journal of Mine Automation,2023,49(2):56-62,76.
[19]	舒亮,张洁,陈璇,等. 面向大规模场景的数字孪生模型快速渲染方法[J]. 计算机集成制造系统,2022,28(11):3664-3672. SHU Liang,ZHANG Jie,CHEN Xuan,et al. Fast rendering method of digital twin model for large scale scenes[J]. Computer Integrated Manufacturing Systems,2022,28(11):3664-3672.
[20]	龚平,何岭松,高鹏宇. 一种XML格式的数字孪生制造系统数据传输协议[J]. 制造业自动化,2023,45(3):70-75. GONG Ping,HE Lingsong,GAO Pengyu. A data transmission protocol of digital twin manufacturing system in XML format[J]. Manufacturing Automation,2023,45(3):70-75.
[21]	高蕾,李江. 基于AMESim液压支架液压系统仿真[J]. 煤炭技术,2023,42(3):264-267. GAO Lei,LI Jiang. Simulation of hydraulic system for hydraulic support based on AMESim[J]. Coal Technology,2023,42(3):264-267.