基于小波分析的转子故障信号自适应降噪技术研究

陈果

基于小波分析的转子故障信号自适应降噪技术研究

陈果

南京航空航天大学民航学院, 南京 210016

基金项目: 国家自然科学基金(50705042);航空科学基金(2007ZB52022)

计量
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- 被引次数: 0
出版历程
- 收稿日期: 2006-12-30
- 修回日期: 2007-04-09
- 刊出日期: 2008-01-28

Research on self-adaptive de-noising technique for rotor faults signal based on wavelet analysis

CHEN Guo

College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

摘要

摘要: 在转子故障信号的小波降噪研究中,降噪效果常常依赖小波分解层数、故障转子转速和信号的采样频率,难于自动完成.针对该问题,提出了一种转子故障信号的自适应小波降噪新方法,该方法先对原始数据进行重采样,然后将重采样信号用小波变换分解到规定的层数,最后运用Donoho软阈值法实现降噪.该方法无需人为选取小波分解层数,降噪过程自动完成.大量的仿真和实验算例验证了方法的正确有效性.
- 航空、航天推进系统 /
- 小波分析 /
- 降噪 /
- 转子 /
- 故障诊断
Abstract: In the current research on wavelet de-noising for rotor faults signal,the denoising effect often depends on the decomposing layer number,rotor rotating speed and signal sampling frequency.But,the de-noising process can not be realized automatically.For this reason,a new self-adaptive de-noising method for rotor fault signal was developed.Firstly,original data was re-sampled,secondly,re-sampled signal was decomposed to given layer number,finally,de-noising was achieved by Donoho soft threshold method.The de-noising process can be performed automatically without manual selection of decomposing layer number.Anumber of examples from simulation and experiments verify the efficiency of this new method.
- aerospace propulsion system /
- wavelet analysis /
- de-noising /
- rotor /
- fault diagnosis

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参考文献(9)

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