摘要
为了能有效地识别滚动轴承故障信号的非平稳和调制特点,提出了一种基于小波分析和Hilbert谱分析的滚动轴承故障诊断的新方法。使用小波分析对包含故障信息的信号进行分解、重构。进一步应用Hilbert变换进行解调和细化频谱分析。结果表明,小波分析和Hilbert变换的联合能够有效地提取故障特征频率并判断故障类型,非常适合滚动轴承的故障诊断。
In order to detect the fault signal of rolling bearings which is the unstable and modulation features,a new method was presented by combining wavelet analysis with Hilbert spectrum analysis. The signal containing fault information is decomposed and reconstructed by using wavelet analysis. Hilbert transform was applied to demodulate and subdivide the frequency analysis. The result show that it is effective in detecting characteristic frequency of fault signals and judging the mode of the bearing fault, so the method suits for the fault diagnosis of roller bearing.
出处
《煤矿机械》
北大核心
2013年第7期293-295,共3页
Coal Mine Machinery
基金
陕西省教育厅专项科研计划项目(2010JK619)
