Semi Solid MR Coal Mine Tunneling Machine Operation Training System
DOI:
https://doi.org/10.54097/08cn4211Keywords:
Mixed Reality Technology, Tunnel Boring Machine Training, Attitude RecognitionAbstract
At present, the coal mining industry is increasingly focusing on improving safety and operational efficiency, which has led to an increasing demand for training of coal mine excavation equipment operators, and the corresponding training costs have also increased. To alleviate these pressures, researching a training program for cantilever tunneling machines based on digital twin technology has become an innovative initiative. This article constructs a virtual environment for underground tunnels by combining mixed reality technology with physical entities. The operator commands the activities of the virtual tunneling machine through actual control of the equipment, and the system evaluates the operation process by tracking and analyzing the operator's posture, ultimately generating detailed evaluation scores. This innovative training model not only greatly enriches the user training experience, but also provides comprehensive data support, which helps to improve the skills and work efficiency of operators, and meets the new requirements and development trends of coal mine safety production.
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References
Promulgation of the Regulations on Coal Mine Safety Production [J]. China Coal Industry,2024(03):34.
Zhao Zhongqiang. Coal mine roadway construction present situation and development trend of technology and equipment [J]. Energy and energy conservation, 2024, (01) : 200-203. The DOI: 10.16643 / j. carol carroll nki. 14-1360 / td. 2024.01.012.
HOU Lei. Design and Application of Intelligent Monitoring System of Coal Mine cantilever boring Machine [J]. Jiangxi Coal Science and Technology,2024, (01):181-183.
Cao Yu. The application of digital twin control system in coal mine machine [J]. Journal of coal mine machinery, 2024, (01) : 179-181. The DOI: 10.13436 / j. m KJX. 202401055.
Zhang Xuhui, Yang Wenjuan, Xue Xusheng, et al. Remote intelligent coal mine tunneling face challenge and research progress [J]. Journal of coal, 2022,47 (01) : 579-597. The DOI: 10.13225 / j. carol carroll nki JCCS. Yg21.1941.
Yu Yang, Wu Lei, Liang Huaqiang. Virtual simulation system of tunnel boring machine design and training mode study [J]. Journal of experimental technology and management, 2018, 35 (11): 141-143 + 148. DOI: 10.16791 / j.carol carroll nki SJG. 2018.11.032.
Zhang Qianwen. Remote virtual machine automatic cutting control system applied research [J]. Mechanical management development, 2023, 38 (01) : 206-207 + 210. DOI: 10.16525 / j. carol carroll nki cn14-1134 / th. 2023.01.082.
WU Chun. Research on Remote Control System of boring machine based on Virtual Reality Technology [J]. Mechanical management development, 2019 (11): 229-230 + 235. DOI: 10.16525 / j. carol carroll nki cn14-1134 / th. 2019.11.096.
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