Automatic operation and manual intervention analysis system for intelligent fully mechanized caving face
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摘要: 智能综放开采不仅要考虑采煤机割煤，还要综合考虑支架后部放煤及顶煤回收情况。相比智能综采工作面，智能综放工作面设备数量更多、工况更加复杂，生产过程中出现异常的可能性更大，导致人工远程干预更多。为保障智能综放开采的顺利运行，设计了智能综放工作面自动运行与人工干预分析系统。给出了智能综放工作面自动化率及放煤工作面控制系统开机率、液压支架自动跟机移架率、采煤机记忆割煤率、自动放顶煤率等关键指标的定义，通过采集综放工作面各主要设备运行信息和采煤信息，判断各设备运行状态，实现综放工作面自动化率统计分析。根据综放工作面自动化运行状态门限知识信息和设备工作流程，建立智能综放工作面自动化运行状态变更的状态门限知识库，用于识别人工干预前的生产设备状态，判断是否符合生产设备解除自动化运行条件。基于对专家知识的深入分析形成规则库，当实施人工干预控制时，自动基于规则库中的规则判断是否符合解除自动化运行的条件，并分析人工干预原因。实际应用结果表明，该系统能够评估智能综放工作面自动化率并分析人工干预原因，为生产系统控制逻辑的优化提供依据。Abstract: In the context of intelligent fully mechanized caving and mining, it is important to consider not only the cutting by the shearer, but also the coal caving at the back of the support and top coal recovery. Compared with intelligent fully mechanized mining face, the characteristic features of intelligent fully mechanized caving face are having more equipment, more complicated working conditions, more possibilities of abnormalities in the production process and more manual remote interventions. In order to ensure the smooth operation of intelligent fully mechanized caving and mining, automatic operation and manual intervention analysis system for intelligent fully mechanized caving face is designed. The definitions of key indicators are defined, such as the automation rate of intelligent fully mechanized caving face and the operation rate of the caving face control system,the shifting rate of automatic following machine of the hydraulic support, shearer memory cutting rate and automatic roof coal caving rate. By collecting the operation information of the main equipment in fully mechanized caving face and the coal mining information, the operation status of each equipment is reviewed and the statistical analysis of automation rate of fully mechanized caving face is obtained. Based on the threshold knowledge information and equipment work-flow of the automatic operation status of fully mechanized caving face, threshold knowledge database of the automatic operation state change of intelligent fully mechanized caving face is established. The database is used to identify the status of production equipment before manual intervention and estimate whether it is suitable to stop automatic operation of production equipment. Based on the in-depth analysis of expert knowledge, a rule database is established. When implementing manual intervention, the database automatically estimates whether the conditions for removing automation are met based on the rules in rule database, and analyzes the reasons for manual intervention. The results show that the system is able to evaluate the automation rate of intelligent fully mechanized caving face, analyze the reasons for manual intervention, and provide a basis for optimizing the control logic of production system.
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期刊类型引用(11)
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