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李 森,李重重,刘 清. 基于透明地质的综采工作面规划截割协同控制系统[J]. 煤炭科学技术,2023,51(4):175−184

. DOI: 10.13199/j.cnki.cst.2022-0514
引用本文:

李 森,李重重,刘 清. 基于透明地质的综采工作面规划截割协同控制系统[J]. 煤炭科学技术,2023,51(4):175−184

. DOI: 10.13199/j.cnki.cst.2022-0514

LI Sen,LI Zhongzhong,LIU Qing. Planned cutting and collaborative control system for fully-mechanized mining face based on transparent geology[J]. Coal Science and Technology,2023,51(4):175−184

. DOI: 10.13199/j.cnki.cst.2022-0514
Citation:

LI Sen,LI Zhongzhong,LIU Qing. Planned cutting and collaborative control system for fully-mechanized mining face based on transparent geology[J]. Coal Science and Technology,2023,51(4):175−184

. DOI: 10.13199/j.cnki.cst.2022-0514

基于透明地质的综采工作面规划截割协同控制系统

Planned cutting and collaborative control system for fully-mechanized mining face based on transparent geology

  • 摘要: 随着煤矿智能化逐步应用开来,透明地质技术成为智能化开采的重要技术支撑之一。针对当前透明地质技术成果在智能开采应用中与装备控制集成融合度不高的问题,研发了基于透明地质的综采工作面规划截割协同控制系统。该系统以智能规划中心和开采控制中心为核心,智能规划中心以地质模型等数据为依据,生成截割模板和控制策略;开采控制中心负责协同控制综采装备,依据截割模板执行控制策略。阐述了系统的两项关键技术,截割模板规划技术和综采装备协同控制技术。截割模板规划技术包括滚筒高度规划和截割工艺段规划。滚筒高度规划采用基于趋势分解与机器学习的滚筒高度预测方法,生成规划高度模板;截割工艺段规划根据单个工艺段的特征,结合中部和端头的截割工艺,形成了工艺段规划表。综采装备协同控制技术包括采煤机支架协同控制和煤流负荷协同控制。采煤机支架协同控制提出了截割前工艺适配和截割中实时调整的控制策略,保证采煤机运行时,支架能够自动跟机作业;煤流负荷协同控制提出了基于线性规划的控制方法,推导出采煤机速度的线性规划函数,用以调整采煤机的速度实现煤流负荷平衡。现场应用和试验表明:采煤机按照规划截割工艺自动执行,试验过程中每刀人工干预次数最大值为25次,人工干预次数下降64.28%~68.75%,刮板输送机负荷平稳可控,没有空载或停机现象。研究成果为智能化开采进一步提升提供了一定的参考价值。

     

    Abstract: With the gradual widespread application of intelligent coal mine, the geological transparency technology has become one of the important technical supports for intelligent mining. Aiming at how to use transparent geological technology achievements to control, equipment an intelligent collaborative mining planning system based on transparent geology was developed. The system is centered on intelligent planning center and mining control center. The intelligent planning center generates cutting templates and control strategies based on geological models. The mining control center collaborates with fully mechanized mining equipment to implement control strategies according to cutting templates. The system consists of two key technologies, namely cutting template planning technology and equipment collaborative control technology. Cutting template planning technology include drum height planning and cutting process planning. Drum height planning uses a forecasting method based on time series trends and machine learning.Cutting process planning defines the characteristics of individual process segments and form a process section planning table. Equipment collaborative control technology include collaborative control of shearer and support and coal flow load collaborative control. Collaborative control of shearer and support proposed a planning strategy, including process adaptation before cutting and real-time adjustment during cutting, so as to ensure the support can complete the automatic follow-up operation. Coal flow load collaborative control proposes a method based on linear programming to adjust the speed of shearers to achieve the balance of coal flow load. The field application and experiments shows that the shearer automatically implements the cutting process according to the plan. The maximum number of manual intervention is only 25 times per cut and the number of manual intervention is significantly reduced by 64.28%—68.75%. The current curve of the conveyor is stable and there is no no-load or stop phenomenon. It has certain reference significance for the further improvement of intelligent mining.

     

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