矿井主通风机和带式输送机远程故障诊断系统  被引量:2

Remote Fault Diagnosis System for Mine Main Ventilator and Belt Conveyor

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作  者:孙晋璐 宋江勇 张唐圣 Sun Jinlu;Song Jiangyong;Zhang Tangsheng(School of Intelligent Manufacturing Engineering,Shanxi Institute of Science and Technology,Jincheng 048006,China)

机构地区:[1]山西科技学院智能制造工程学院,山西晋城048006

出  处:《煤矿机械》2024年第8期166-169,共4页Coal Mine Machinery

基  金:山西科技学院科研基金项目(XKY018)。

摘  要:针对矿井大型设备点巡检方式存在的数据及时性和真实性难以保证、无法持续跟踪数据预知设备状态的问题,设计了主通风机和带式输送机远程故障诊断系统。建立了包含数据采集层、传输层、应用层的总体架构,采用OMAPL138微处理器为核心设计了监测分站进行数据采集和上传。基于B/S架构建立了系统软件,提出了基于工况的自学习诊断模型智能报警判断策略和具有冗余特性的多节点数据存储方式,并建立了设备现场-矿端服务器-诊断中心三级管理模式。在寺河矿的应用验证了该系统的有效性和可靠性,诊断准确率可达90%以上。Aiming at the problems that the point inspection method of large mine equipment is difficult to guaranteedata the timeliness and authenticity of data,and it is unable to continuously track the data to predict the status of equipment,an remote fault diagnosis system for main ventilator and belt conveyor was designed.The overall architecture of data acquisition layer,transmission layer and application layer was established,a monitoring substation based on OMAPL138 microprocessor for data acquisition and uploading was designed.Built the system software based on B/S architecture,an intelligent alarm judgment strategy for self-learning diagnosis model based on working conditions and a multi-node data storage method with redundant characteristics were proposed,and a new three-level management mode of field equipment-mine server-diagnostic service center was established.The application in Sihe coal mine verifies the effectiveness and reliability of the system,and diagnostic accuracy can reach more than 90%.

关 键 词:大型设备 远程故障诊断 智能报警 数据存储 设备管理 

分 类 号:TD67[矿业工程—矿山机电]

 

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