Digital twin: meeting the technical challenges of intelligent fully mechanized working face
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摘要: 基于智能化综采工作面目标任务−自主完成综采工作面可靠割煤、保持工作面几何关系、顶板可靠支护，提出了综采工作面智能控制关键技术，包括采煤机定位技术、工作面可视化技术、液压支架电液控制技术（装置）、工作面通信技术、综采装备协同控制技术、采煤机自动调高技术、工作面自动调直技术和工作面围岩支护控制技术（其中前3种技术属于智能化综采工作面的感知与执行层，工作面通信技术是智能化综采工作面的传输层，后4种技术属于智能化综采工作面的决策层）。指出智能化综采工作面面临的挑战为决策层的自主决策能力不能适应复杂多变的工况、感知与执行层不能支撑决策层的信息需求和决策指令的可靠执行。针对上述挑战问题，采用基于仿真的数字孪生建模方法，提出了综采工作面数字孪生系统架构。综采工作面数字孪生系统虚拟实体包括机理模型和行为模型，利用综采装备机理模型可获得综采装备物理系统的不可测数据，行为模型可为综采工作面智能控制系统提供反映物理装备运行状态的全息信息，解决决策层数据信息匮乏问题；综采装备机理模型与其控制系统组合的离线运行模式形成综采工作面硬件在环仿真系统，为基于工艺规则的智能控制算法提供测试平台；综采装备机理模型、行为模型与其控制系统组合的离线运行模式形成综采工作面计算实验系统，为综采工作面智能控制系统真正的自主决策复杂算法开发提供测试平台。Abstract: The goal and task of intelligent fully mechanized working face are to independently complete the reliable coal cutting of the fully mechanized working face, maintain the geometric relationship of the working face and reliable roof support. According to the goal and task, the key technologies of intelligent control of fully mechanized working face are proposed. The technologies include shearer positioning technology, working face visualization technology, hydraulic support electro-hydraulic control technology (device), working face communication technology, collaborative control technology of fully mechanized mining equipment, autonomous height adjustment technology of shearer, autonomous straightening technology of working face and surrounding rock support control technology of working face. Among these technologies, the first three technologies belong to the perception and execution layer of intelligent fully mechanized working face. The working face communication technology is the transmission layer of intelligent fully mechanized working face. And the last four technologies belong to the decision-making layer of intelligent fully mechanized working face. The challenges faced by the intelligent fully mechanized working face are pointed out, which are that the autonomous decision-making capability of the decision-making layer cannot adapt to the complex and changeable working conditions, and the perception and execution layer cannot support the information demand of the decision-making layer and the reliable execution of the decision-making instructions. In order to solve the above challenges, the digital twin system architecture of fully mechanized working face is proposed by use of the simulation-based digital twin modeling method. The virtual entity of the digital twin system of the fully mechanized working face comprises a mechanism model and a behavior model. The unmeasurable data of a physical system of the fully mechanized working face equipment can be obtained by the mechanism model. The behavior model can provide holographic information reflecting the running state of the physical equipment for an intelligent control system of the fully mechanized working face. Thus the problem of the lack of data information in the decision-making layer is solved. The off-line run mode of the combination of the mechanism model of fully mechanized mining equipment and its control system forms the hardware in the loop simulation system of fully mechanized working face, which provides a test platform for intelligent control algorithms based on process rules. The off-line run mode of the combination of the mechanism model, behavior model and its control system of the fully mechanized mining equipment forms the calculation experimental system of the fully mechanized working face, which provides a test platform for the development of the real independent decision-making complex algorithm of the intelligent control system of the fully mechanized working face.
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图 7 综采工作面数字孪生系统架构
Figure 7. Digital twin system architecture of fully mechanized working face
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