摘要:
目前开发的综采设备远程故障诊断系统大多是针对采煤机、刮板输送机、带式输送机等单机设备，以及基于视频或虚拟现实的专家远程指导维护系统，而集云平台、远程故障诊断和专家远程指导维护于一体的设备群故障诊断系统研究很少。针对该问题，设计了一种基于云平台的综采设备群远程故障诊断系统。首先通过传感器采集综采工作面采煤机、液压支架、刮板输送机、转载机、乳化液泵站、带式输送机及供电系统等的状态监测信息；然后通过煤矿井下环网将综采设备群运行状态监测信息传输到地面服务器，地面服务器对接收到的信息进行智能故障诊断分析、数据存储、报警查询等；最后通过MQTT协议将地面服务器的综采设备群状态监测信息按照统一格式传输至云服务器进行数据处理及格式转换，并将转换后的数据利用4G/5G网络传输至移动端和通过MQTT协议传输到PC端，从而实现综采设备群运行状态监测的可视化、故障查询、故障报警及故障预警信息的及时推送。以可视化视频监控为媒介，当综采设备出现故障时，视频信息可实时转接至对应专家，专家通过视频信息远程指导井工人员进行远程维护。该系统在陕西黄陵煤矿综采工作面进行了测试，结果表明：该系统实现了综采工作面设备群的远程故障诊断，通过手机移动平台可以实现综采工作面设备群运行状态实时监测和故障预警信息的及时推送，降低了综采工作面设备群的故障率和非计划停机次数，生产效率提高了约30％。
Abstract:
The currently developed remote fault diagnosis systems for fully mechanized mining equipment are mostly for single-machine equipment such as coal shearers, scraper conveyors and belt conveyors, and for expert remote guidance and maintenance systems based on video or virtual reality. However, there is few research on equipment group fault diagnosis systems that integrates cloud platform, remote fault diagnosis and expert remote guidance and maintenance. In order to solve the above problem, a remote fault diagnosis system of fully mechanized mining equipment group based on cloud platform is designed. Firstly, the method collects the state monitoring information of shearer, hydraulic support, scraper conveyor, transfer machine, emulsion pump station, belt conveyor and power supply system of fully mechanized working face through sensors. Secondly, the state monitoring information of fully mechanized mining equipment group is transmitted to the ground server through the underground ring network of the coal mine. The ground server performs intelligent fault diagnosis analysis, data storage, and alarm query on the received information. Finally, the state monitoring information of fully mechanized mining equipment group of the ground server is transmitted to the cloud server in a unified format through the MQTT protocol for data processing and format conversion. And the converted data is transmitted to the mobile terminal by 4G/5G network and transmitted to the PC terminal by the MQTT protocol. Therefore, the method can realize the visualization, fault query, fault alarm and timely push of fault warning information of the state monitoring of fully mechanized mining equipment group. With visual video monitoring as the medium, when the fully mechanized mining equipment fails, the video information can be transferred to the corresponding expert in real time. The expert can remotely guide the coal workers for remote maintenance through the video information. The system has been tested in the fully mechanized working face of Huangling Coal Mine in Shaanxi. The results show that the system realizes the remote fault diagnosis of fully mechanized mining equipment group. The system realizes the real-time push of the state monitoring and fault warning information of fully mechanized mining equipment group through the mobile phone platform. Moreover, the system reduces the fault rate and the number of unplanned shutdowns of fully mechanized mining equipment group and improves the production efficiency by about 30%.
百度学术
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