摘要
利用小波变换理论的基本原理,对车载发动机泵机组中轴承的故障信号进行了处理,实测信号经小波分解和重构后,能有效地提取其中的信号特征。实验结果证明,小波分析能够根据被分析的信号特征,自适应地选择相关的频带,提高信号的时-频分辨率,突出故障信息,实现早期故障的高效诊断。
Based on primary theory of wavelet transformation, the signal of bearing fault in vehicle-load engine pump machine was processed. The signal characteristic can be effective withdrawn from the actual signal after wavelet decomposition and restructuring. The experimental result proves that, the wavelet analysis can adaptively choose the related frequency band according to the analyzed signal characteristic, enhance the time-frequency resolution of the signal, give the fault information, and realize early highly effective fault diagnosis.
出处
《机床与液压》
北大核心
2007年第11期183-184,190,共3页
Machine Tool & Hydraulics
关键词
小波
故障诊断
发动机泵机组
Wavelet
Fault diagnosis
Engine pump machine
