基于工业互联网架构的煤矿瓦斯智能抽采管控系统设计

Design of coal mine gas intelligent extraction control system based on industrial Internet architecture

  • 摘要: 目前煤矿瓦斯智能抽采管控系统存在以下问题:①系统功能局限于某一段流程管控,导致瓦斯抽采业务管理覆盖不全、措施落实不到位。② 基于传统的“烟囱式”IT架构,导致子系统分散、数据利用率低、协同能力差,后期子系统融合代价大、系统扩展不便。③ 瓦斯抽采过程仍存在较多的人工环节,系统智能化、自动化能力还有待进一步提升。针对上述问题,设计了一种基于工业互联网架构的煤矿瓦斯智能抽采管控系统。基于发布/订阅模式开发了瓦斯抽采多源异构数据采集流程,促进了数据的解耦和共享,降低了系统复杂度,实现了瓦斯抽采管网数据、钻孔作业及轨迹数据、设备工况数据、达标评判数据等多源异构数据的统一采集。基于数字孪生技术,构建了三维抽采系统模型,达到了井上下抽采系统的立体化展示。基于规则引擎技术,根据订阅的Topic对经过消息中心处理后的传感器数据进行判断,可进行告警消息的推送,并将处理后的传感器数据存入数据库中,以实现瓦斯抽采达标评判的自动化、流程化运行。利用机器视觉视频分析技术识别钻杆根数,从而实现钻孔过程的钻杆根数(钻孔深度)的自动计数和钻孔工程的信息化管理,结合钻孔测量仪器,实现了钻孔轨迹左右、上下偏差分析及可视化。现场应用结果表明:瓦斯抽采相关管理人员通过查看瓦斯智能抽采管控系统软件,可实时快速地了解各抽采面抽采情况、抽采评判情况、钻孔工程施工情况、系统故障情况,提高了瓦斯抽采信息化和智能化管理水平。

     

    Abstract: There are currently problems with the intelligent gas extraction system in coal mines. ① The system's functions are limited to a certain process control, resulting in incomplete coverage of gas extraction business management and inadequate implementation of measures. ② Based on the traditional "chimney style" IT architecture, subsystems are scattered, data utilization is low, collaborative capabilities are poor. The cost of later subsystem integration is high, making system expansion inconvenient. ③ There are still many manual links in the gas extraction process, and the system's intelligence and automation capabilities still need to be further improved. In order to solve the above problems, a coal mine gas intelligent extraction control system based on industrial Internet architecture is designed. A multi-source heterogeneous data collection process for gas extraction has been developed based on the publish/subscribe model. It promotes data decoupling and sharing, reduces system complexity, and achieves unified collection of multi-source heterogeneous data such as gas extraction pipeline network data, drilling operation and trajectory data, equipment working condition data, and meeting standard evaluation data. Based on digital twin technology, a three-dimensional extraction system model is constructed, achieving a three-dimensional display of the up and down extraction system. Based on rule engine technology, sensor data processed by the message center can be judged based on subscribed Topic. The processed sensor data is stored in the database to realize the automation and process operation of gas extraction standard evaluation. By using machine vision video analysis technology to identify the number of drill pipes, automatic counting of drill pipe numbers (drilling depth) during the drilling process and information management of drilling engineering are achieved. Combined with drilling measurement instruments, analysis and visualization of drilling trajectory left and right, upper and lower deviations are achieved. The on-site application results show that gas extraction management personnel can quickly and in real time understand the extraction situation, extraction evaluation, drilling engineering construction, and system failure of each extraction face by viewing the intelligent control system software for gas extraction. It improves the level of gas extraction information and intelligent management.

     

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