Research on the "shape-performance-control" integrated digital twin system for boom-type roadheaders

Author:

Zhang Jianzhuo,Wan Chuanxu,Wang Jie,Chen Ce,Wang Tao,Zhang Runfeng,Guo Hao

Abstract

AbstractThe boom-type roadheader plays a crucial role in coal mining. However, conducting the real-time monitoring of the mechanical performance and comprehensive adaptive cutting in the dynamic cutting process are challenging. To address these issues, a digital twin system that integrates the elements of “shape, performance, and control” for roadheaders is presented in this paper. The system comprises three components: physical space, service space, and twin space. The service space forms the core of the entire system. Within this space, twin models and control models are created using numerical simulation, artificial intelligence and multi-source data fusion technology. These models serve the purpose of predicting the roadheader’s mechanical performance and controlling the swing speed of the cutting arm. The physical space is built using technologies such as robot kinematics, electrical systems, hydraulic transmission, and other relevant techniques. This approach facilitates the transmission of multi-sensor data to twin models. The control model then manages the roadheader’s function based on the output signals from the control model. The twin space is constructed utilizing physical rendering engines, databases, and 3D modelling tools. This space visualizes and stores the movement, performance, and control parameters of the roadheader. The results demonstrate that the average absolute error between the measured data from the test’s three position strain gauges and the predicted data from the twin system is 10.38 MPa. Furthermore, the twin system achieves an average update interval of 0.34 s, allowing real-time stress monitoring of the structural components of the roadheader and preventing damage caused by overload. The proposed control model enables adaptive adjustment of the swing speed of the cutting arm in approximately 0.3 s. This improvement significantly enhances the adaptive cutting capabilities of roadheaders when dealing with complex coal and rock formations.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Reference29 articles.

1. Wang, J. Development and prospect on fully mechanized mining in Chinese coal mines. Int. J. Coal Sci. Technol. 1(3), 253–260 (2014).

2. Zhiqiang, L. et al. Analysis of key technology and research path of full section boring machine for 1000 m vertical shaft with hard rock strata. J. China Coal Soc. 47(08), 3163–3174 (2022).

3. Hargrave, C. O., James, C. A. & Ralston, J. C. Infrastructure-based localisation of automated coal mining equipment. Int. J. Coal Sci. Technol. 4(3), 252–261 (2017).

4. Dolipski, M., Cheluszka, P. & Sobota, P. Investigating the simulated control of the rotateonal speed of roadheader cutting heads, relating to the reduction of energy consumption during the cutting process. J. Min. Sci. 51(2), 298–308 (2015).

5. Hui, W., Zhen, W. & Di, W. A machine speed regulation system of the constant power based on RBF neural network PID control. Meas. Control Technol. 34(11), 67–69 (2015).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3