摘要
利用小波包理论的基本原理,对滚动轴承的故障信号进行了处理,实测信号经小波包分解和重构后,应用Hilbert变换进行包络解调和细化频谱分析,得出故障信号所对应的频谱。试验结果证明,对滚动轴承的非平稳信号进行小波包的Hilbert变换和细化频谱分析,并进行故障诊断是行之有效的,这为旋转机械的故障诊断提供了新的参考,具有重要的实际工程应用价值。
Based on primary theory of wavelet packet transformation, the signal of bearing fault was processed, the signal charac-teristic can be effective withdrawn from the actual signal after wavelet packet decomposition and restructuring. Then, using Hilbert transform and time/frequency-domain bearing vibration analysis, it presents an approach to get the frequency of fault signal. The experimental result proves that, the wavelet packet analysis can adaptively choose the related frequency band according to the ana- lyzed signal characteristic, the practice example shows that this method is effective. The research results provide the theoretical foundation for rotary machine fault diagnosis, and have important practical value.
出处
《现代制造工程》
CSCD
北大核心
2012年第11期121-125,共5页
Modern Manufacturing Engineering
基金
山西省自然科学基金项目(2008012006-3)
山西省教育厅高校科技开发项目(2007136)
