作　　者： ; ; ; ; ; (皇雅斌）; (杨青）;

机构地区： 西南石油大学电气信息学院

出　　处： 《仪表技术与传感器》 2014年第3期107-110,共4页

摘　　要： 故障诊断对旋转机械的安全运行有十分重要的意义。针对小波分析在机械故障诊断应用中对信号高频部分的频率分辨率较弱的问题,提出利用小波包分析提取振动信号频带的能量特征,建立起振动信号各频带能量到旋转机械各故障状态间的映射关系。对待检信号进行小波包重构,利用待检状态的特征向量与典型故障特征表,提出采用贴近度来进行模糊模式识别的方法进行旋转机械故障诊断。实际诊断结果表明:该方法能够有效诊断出旋转机械与对应频率相关的早期微弱故障征兆。该诊断方法可用于高速旋转机械故障诊断场合。 The fault diagnosis is very vital for the safe operation of rotating machinery.The resolution of high frequency part of signal frequency in application of wavelet analysis of mechanical fault diagnosis is weak,this paper proposed extracting fault eigenvectors of rotating machinery by using wavelet packet analysis band energy feature,set up the band energy to vibration signal of rotating machinery fault between the state of the mapping relationship.Reconstruct wavelet packet for signal,the use of the characteristics of state vector and typical fault feature table,the paper proposed the closeness to fuzzy pattern recognition method for rotating machinery fault diagnosis.The experiment results show that the method can diagnose the fault of rotating machinery effectively.This fault diagnosis method is widely used in high speed rotating machinery.

关 键 词： 旋转机械 故障诊断 小波包变换 贴近度

领　　域： [电子电信] [电子电信]