铜钪金属矿重载机械故障检测与智能诊断技术的研究  

Research of Fault Detection and Intelligent Diagnosis Technology of Heavy-loading Machinery in Copper-scandium Metal Mine

作　　者：张国伟[1] 

机构地区：[1]广西机电职业技术学院,广西南宁530007

出　　处：《工矿自动化》2011年第8期34-37,共4页Journal Of Mine Automation

摘　　要：通过对煤炭矿山关键设备故障检测与智能诊断技术的分析研究,结合铜钪金属矿的设备状况,分析了将煤矿技术应用于金属矿山的可行性,探讨了铜钪金属矿山关键设备核心部件故障检测与智能诊断的研究方法与策略、故障信号特征的提取方法以及设备状态评估与定量诊断方法。该文为推进金属矿山减排及资源化利用技术研究具有参考意义。By analyzing fault detection and intelligent diagnosis technologies of key devices of coal mine and combining with equipments condition in copper-scandium metal mine,the paper analyzed application feasibility of coal mine technologies to metal mine,and discussed research methods and strategy,extraction methods of fault signal characteristics and methods of evaluation and quantify diagnosis of equipment state of fault detection and intelligent diagnosis of key devices in copper-scandium mine.The paper has great reference value in promoting technology research of emission reduction and rational source utilization in metal mine.

关 键 词：铜钪金属矿 重载机械 振动监测 故障检测 智能诊断 提升小波构造 

分 类 号：TD164[矿业工程—矿山地质测量]