煤矿机电设备故障诊断与预测维护技术研究  

Research on Fault Diagnosis and Predictive Maintenance Technology for Coal Mine Mechanical and Electrical Equipment

作　　者：代存海 陈一[1] Dai Cunhai;Chen Yi(Huafeng Coal Mine,Xinwen Mining Industry Group Co.,Ltd.,Tai'an 271413,China)

机构地区：[1]新汶矿业集团有限责任公司华丰煤矿,山东泰安271413

出　　处：《山东煤炭科技》2025年第4期189-192,共4页Shandong Coal Science and Technology

摘　　要：煤矿机电设备的高故障率和高维护成本问题严重制约了设备的可靠性和管理效率。研究旨在探讨故障诊断与预测维护技术的应用,通过对煤矿机电设备的分类和常见故障类型的分析,提出一种基于信号处理的实时监测技术和数据驱动的故障诊断方法,构建结合状态监测与历史数据的预测维护模型,通过实时监测设备运行状态,提前识别潜在故障。实验结果表明,该模型有效降低了设备故障率,维护成本减少约25%,并通过优化资源配置提升了设备管理效率,为煤矿机电设备的管理提供了理论依据与实践指导。The high failure rate and maintenance cost of coal mine electromechanical equipment seriously affect the reliability and management efficiency of the equipment.The research aims to explore the application of fault diagnosis and predictive maintenance technology.Through the classification of coal mine electromechanical equipment and analysis of common fault types,a real-time monitoring technology based on signal processing and data-driven fault diagnosis method are proposed.A predictive maintenance model combining state monitoring and historical data is constructed to identify potential faults in advance through real-time monitoring of equipment operating status.The experimental results show that the model effectively reduces equipment failure rate,reduces maintenance costs by about 25%,and improves equipment management efficiency by optimizing resource allocation,providing theoretical basis and practical guidance for the management of coal mine electromechanical equipment.

关 键 词：煤矿机电设备 故障诊断 预测维护 

分 类 号：TD407[矿业工程—矿山机电]