摘要
讨论了提升小波变换在大型复杂齿轮箱故障信号特征分析的应用。通过实验分析,得出通过提升小波变换不仅可以有效的去除噪声、提高信号信噪比,还可保留原始信号的非线性特征,有利于后期故障特征提取的精确性。
In order to improve the ability of fault identification in large complex gear box, an approach based on lifting wavelet transform（LWT） is proposed. Through the experimental analysis, the method can remove noise effectively and improve the signal to noise ratio, meanwhile retain the original signal nonlinear characteristic. It would be beneficial to feature extraction in fault diagnosis.
出处
《机电设备》
2015年第6期14-16,20,共4页
Mechanical and Electrical Equipment
关键词
形态提升小波
特征提取
故障诊断
lifting wavelet transform
feature extraction
fault diagnosis
