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基于信息物理融合系统(CPS)的综采单元实时数据感知节点与信息建模

Design of real-time data perception nodes and information models for mechanized-mining cells based on cyber-physical system (CPS)

  • 摘要: 随着煤矿智能化转型战略的深入,煤矿综采单元(Fully Mechanized-Mining Cells,FMMC)作为实现高效智能化开采的核心环节,其发展正面临多源异构资源管理复杂、数据语义不一致及实时感知能力不足等挑战。为解决上述问题,设计了一种基于信息物理融合系统(Cyber-Physical System, CPS)的体系框架,聚焦于实时数据感知节点与信息模型的构建,以提升FMMC的资源协同能力、数据集成效率与智能决策水平。主要内容包括:首先,在明确FMMC由采煤机、液压支架、刮板输送机等核心设备及传感器网络、控制系统等辅助设备构成的基础上,引入具有动态配置策略的CPS节点,实现资源交互和数据实时感知,进而提出了面向FMMC的CPS节点通用信息模型,并基于基本信息、必要资源、辅助资源和人力资源等多层次结构,构建了统一的语义描述框架,为多源异构数据的语义一致性提供理论支持;其次,采用本体建模对设备、资源及其相互关系进行形式化描述,构建了基于本体的FMMC异构资源语义统一描述模型,有效支持设备间的语义一致性与系统互操作性,解决了多设备、多系统间的语义异构问题。在此基础上,构建了基于OPC UA协议的综采数据映射架构模型,实现了从本体语义模型到工业标准协议的无缝对接,保障多设备间数据共享与语义统一,增强了系统的扩展性和互操作能力。最后,通过在X煤矿部署CPS节点,采集FMMC资源信息及过程数据,并开发信息管理与集成分析平台,对本文所提出的实时数据感知节点与信息模型进行了实例化验证。结果表明,该信息模型架构能够显著提升FMMC异构资源的协同管理能力与实时响应能力,在设备监控、动态感知及资源优化配置等方面表现出优越性能。

     

    Abstract: As the intelligent transformation of coal mines progresses, Fully Mechanized-Mining Cells (FMMC), key cells for efficient and intelligent coal mining, face challenges like multi-source heterogeneous resource management, inconsistent data semantics, and limited real-time perception capabilities. This paper designs a Cyber-Physical System (CPS) based system framework covering the construction of real-time data perception nodes and information models to improve the resource coordination capability, data integration efficiency, and intelligent decision-making level of FMMC. The specific contents include: First, the composition and characteristics of the FMMC are clarified, and it is defined as a comprehensive operating cells consisting of core equipment such as shearers, hydraulic supports, and armored chain conveyors, as well as auxiliary devices such as sensor networks and control systems. The resource interaction network creation based on dynamic configuration strategies and real-time perception of resource node data are realized through the introduction of the CPS nodes of the FMMC. A unified semantic description framework is constructed based on the four levels of basic information, necessary resources, auxiliary resources, and human resources, providing theoretical support for the semantic consistency of multi-source heterogeneous data of the FMMC. Secondly, ontology modeling technology is used to further solve the semantic heterogeneity problem among multiple devices and systems in the FMMC. Through the formal description of equipment, resources and their relationships, an ontology-based FMMC heterogeneous resource empowerment semantic unified description model is constructed to provide support for semantic consistency and interoperability among devices. In addition, a FMMC data mapping architecture model based on OPC UA is constructed to achieve seamless connection from the ontology semantic model to the industrial standard protocol, ensuring data sharing and semantic unification among device group, and improving the scalability and interoperability of the system. Finally, the resource and process data of the FMMC at X Coal Mine were collected using CPS nodes. An information management and analysis platform was developed to instantiate and verify the real-time data perception node and information model. Results show that the information model architecture enhances collaborative management, real-time response, and resource optimization, equipment monitoring and dynamic perception.

     

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