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基于數字孿生技術(shù)的大型煤礦遠程智能監控研究
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陜西陜煤榆北煤業(yè)有限公司

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國家自然科學(xué)(61501285)


Research on Remote Intelligent Monitoring of Large Coal Mines Based on Digital Twin Technology
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    摘要:

    為了保證大型煤礦開(kāi)采工作的安全性與質(zhì)量,利用數字孿生技術(shù)優(yōu)化設計大型煤礦遠程智能監控方法。利用數字孿生技術(shù)構建大型煤礦虛擬模型,在該模型下確定測點(diǎn)位置,遠程采集大型煤礦實(shí)時(shí)運行數據。通過(guò)對數據特征的提取與匹配,從煤礦開(kāi)挖設備和施工環(huán)境兩個(gè)方面,監測大型煤礦運行狀態(tài)。改裝大型煤礦遠程智能控制器,以運行狀態(tài)的監測結果作為控制程序的啟動(dòng)條件,實(shí)現對大型煤礦的遠程智能監控任務(wù)。通過(guò)與傳統監控方法的對比得出結論:優(yōu)化設計方法對煤礦開(kāi)挖設備的監控性能明顯升高,對環(huán)境中瓦斯濃度和溫度的監測誤差分別降低了0.34%和0.19℃,控制誤差分別降低0.09%和0.145℃,同時(shí)監控范圍擴大27.4%。

    Abstract:

    In order to ensure the safety and quality of large-scale coal mining work, digital twin technology is used to optimize the design of remote intelligent monitoring methods for large-scale coal mines. Using digital twin technology to construct a virtual model of large-scale coal mines, determine the location of measurement points under this model, and remotely collect real-time operational data of large-scale coal mines. By extracting and matching data features, monitoring the operation status of large coal mines from two aspects: mining equipment and construction environment. Retrofitting a remote intelligent controller for large coal mines, using the monitoring results of operating status as the starting condition for the control program, to achieve remote intelligent monitoring tasks for large coal mines. By comparing with traditional monitoring methods, it can be concluded that the optimized design method significantly improves the monitoring performance of coal mining excavation equipment, reduces the monitoring errors of gas concentration and temperature in the environment by 0.34% and 0.19 ℃, and reduces the control errors by 0.09% and 0.145 ℃, respectively. At the same time, the monitoring range is expanded by 27.4%.

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李偉,葉鷗,劉輝,黃天塵.基于數字孿生技術(shù)的大型煤礦遠程智能監控研究計算機測量與控制[J].,2023,31(11):204-211.

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歷史
  • 收稿日期:2023-05-15
  • 最后修改日期:2023-06-08
  • 錄用日期:2023-06-09
  • 在線(xiàn)發(fā)布日期: 2023-11-23
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