基于谐波小波分析的矿井通风机故障诊断  

Fault Diagnosis for Mine Ventilator Based on Haarmonic Wavelet Analysis

作　　者：冯伟[1] 郑晟[1] 

机构地区：[1]太原理工大学信息工程学院,太原030024

出　　处：《煤矿机械》2014年第5期253-255,共3页Coal Mine Machinery

摘　　要：针对矿井通风机故障信号的动态非平稳、能量微弱等特点,提出基于谐波小波变换的故障诊断方法,克服了传统诊断方法中存在的信号遗漏与频泄现象。以BDK-6-NO18轴流式通风机为研究对象,利用谐波小波变换的优势,成功从振动信号中提取出设备故障特征信号。For vibration signal of mine ventilator is dynamic, non-stationary and weak, a fault diagnosis method based on harmonic wavelet transform is proposed, overcome the phenomenon that signal omission and frequency leakage existing in the traditional diagnosis methods. For BDK-6-NO18 axialflow fan, taking the advantages of harmonic wavelet, extract the fault characteristic signal from vibration signal successfully.

关 键 词：矿井通风机 谐波小波 振动信号 故障诊断 

分 类 号：TD441[矿业工程—矿山机电]