基于数字孪生技术的采煤机运行状态监测

    Monitoring the operational status of coal mining machines based on digital twin technology

    • 摘要: 本文以Matlab Simulink作为核心平台与MapleSim Insight相结合,依据数字孪生技术对采煤机运行状态进行实时监测,涵盖了物理实体、虚拟实体、数据层、服务界面及数据传输。实时数据借由传感器与智能I/O系统加以采集,虚实系统间的数据交互则借助OPC等协议予以实现,最终在MapleSim Insight里达成三维实时监测的可视化。对采煤机30 s运行数据展开测试验证,机身-摇臂角度误差仅为±0.04°,拟合度达98.5%,数据延迟小于0.2 s。此系统能精准、实时地反映采煤机运行状态,契合对复杂采煤机实施监控与仿真的一体化需求。

       

      Abstract: This study utilizes Matlab Simulink as the core platform, integrated with MapleSim Insight, to enable real-time monitoring of the operational status of the coal mine machine based on digital twin technology. The framework encompasses the physical entity, virtual entity, data layer, service interface, and data transmission. Real-time data is collected via sensors and intelligent I/O systems, while data interaction between the physical and virtual systems is achieved through protocols such as OPC. Ultimately, 3D real-time monitoring visualization is realized in MapleSim Insight. Tests conducted with 30 seconds of operational data show that the error in the body-arm angle is only ±0.04°, with a fitting accuracy of 98.5% and a data latency of less than 0.2 seconds. This system accurately and real-timely reflects the operational status of the coal mine machine, meeting the integrated requirements for monitoring and simulating complex coal mine machine operations.

       

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