煤矿采煤工作面数字孪生系统研究与应用
Research and Application of Digital Twin System in Coal Mining Working Face of Coal Mine
张磊 1李绍良 2曲越3
作者信息
- 1. 北京大学鄂尔多斯能源研究院,内蒙古 鄂尔多斯 017000;鄂尔多斯职业学院,内蒙古 鄂尔多斯 017000
- 2. 鄂尔多斯职业学院,内蒙古 鄂尔多斯 017000
- 3. 内蒙古峥创科技有限公司,内蒙古 鄂尔多斯 017004
- 折叠
摘要
针对鄂尔多斯万利一矿 31311 工作面缺乏实时监测和预测能力、视频信号视角有限且有粉尘干扰的问题,提出数字孪生系统,通过物理感知层、数据层、业务逻辑层和表现层构建系统架构,采用光纤、Modbus、CANBUS、Profibus、OPC和无线通信等方式进行数据采集,传感器采集的数据通过PLC、OPC服务器传输至客户端,MQTT用于实时数据转发,MySQL用于历史数据存储.可视化平台基于Unity引擎,结合HTML5、CSS和JavaScript,进行三维建模和渲染,并通过 3ds Max实现高精度轻量化建模.系统成功实现了工作面设备的实时监测、状态反馈和智能控制,解决了传统视频监测可视度低的问题,提高了工作面的自动化水平.系统的实际应用显著提升了工作面的效率与安全性,助力工作面场景数字化转型.
Abstract
In response to the lack of real-time monitoring and prediction capabilities,limited video signal perspectives,and dust interference in the 31311 working face of Wanli No.1 Mine in Ordos,a digital twin system is proposed.The system architecture is constructed through physical perception layer,data layer,business logic layer,and presentation layer,and data collection is carried out using optical fiber,Modbus,CANBUS,Profibus,OPC,and wireless communication methods.The data collected by sensors is transmitted to the client through PLC and OPC servers,MQTT is used for real-time data forwarding,and MySQL is used for historical data storage.The visualization platform is based on the Unity engine,combined with HTML5,CSS,and JavaScript,for 3D modeling and rendering,and achieves high-precision lightweight modeling through 3ds Max.The system has successfully achieved real-time monitoring,status feedback,and intelligent control of the working face equipment,solving the problem of low visibility in traditional video monitoring and improving the automation level of the working face.The practical application of the system has significantly improved the efficiency and safety of the workplace,assisting in the digital transformation of workplace scenarios.
关键词
数字孪生/智慧煤矿/采掘设备/技术路线/平台设计/采煤工作面Key words
digital twin/smart coal mine/mining and excavation equipment/technical route/platform design/coal mining working face引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据