摘要
应用小波包变换理论和小波包降噪原理,对轧机齿轮箱的振动信号进行小波包降噪,有效地从含噪信号中提取出故障特征。通过对计算机仿真信号的降噪效果比较和实例分析,显示了小波包降噪的优越性。最后对齿轮箱降噪前后小波包各频带能量向量的比较,进一步表明了小波包降噪在消除高频干扰,凸显故障特征方面的有效性。
The theory of wavelet packet transform and the principle of wavelet-packet de-noising are used to carry out the wavelet-packet de-noising for the vibration singals of mill gearbox and extract the fault feature from noise singal effectively.Through comparison with the denoising effects of several computer artificial signals and case analysis,the superiority of the wavelet packet de-noising method is verified.Finally,the result of comparison with each wavelet packet frequency band energy vector on the noise and de-noised signals shows that the wavelet packet de-noising method is very effective on eliminating high-frequency interference and fault feature-promi-nence.
出处
《机械制造与自动化》
2010年第3期26-28,共3页
Machine Building & Automation
关键词
振动信号
小波包变换
齿轮箱
降噪
故障特征
频带能量
vibration singals
wavelet-packet transform
mill gearbox
de-noising
fault feature
frequency band energy vector
