摘要
针对传统小波尺度能量谱的不足之处,提出了一种改进型的小波域冲击能量相关技术。首先利用AR时序建模方法,去除振动信号中的周期谐波成分,然后采用连续小波变换将去除周期谐波后的信号分解到每个不同的小波尺度上,并计算不同尺度上小波系数的Teager瞬时能量。在此基础上,利用峭度和循环统计量对不同尺度上的小波Teager能量序列进行尺度筛选,确定能量序列进行尺度积分区间。最后,结合能量序列的时域相关运算,提取出冲击信号的发生周期或频率。结果表明:该方法能降低常规小波尺度能量相关法的误判率,而且在强噪声干扰下能准确地提取出弱冲击信号的发生频率,对旋转机械故障作出准确的判断。
Aiming at disadvantages of a general wavelet energy method,an improved correlative technique for wavelet-domain impact energy was proposed.With this method,AR modeling was used to remove periodic harmonic components from a vibration signal to be analyzed.Then using continuous wavelet transformation,the de-noised signal was decomposed into different wavelet scales.Teager energy operator was used to track the instantaneous energy of each wavelet coefficient.Based on the sensitivity of kurtosis and cyclostatistic to rotating machine impact signal,Teager energy series of wavelet coefficient were screened out and integrated in the scale domain.Finally,the occurring period of impact signals was extracted using the correlative algorithm.The results showed that the proposed method can extract occurring frequency of weak impact in strong noise background and decrease the rate of fault mis-discrimination for rotating machines.
出处
《振动与冲击》
EI
CSCD
北大核心
2012年第12期129-134,共6页
Journal of Vibration and Shock
基金
国家自然科学基金(51005261)
重庆大学211项目(S-09106)
关键词
连续小波变换
TEAGER能量算子
小波尺度能量谱
冲击周期
故障诊断
continuous wavelet transformation
Teager energy operator
wavelet scale-energy spectrum
impact cycle
fault diagnosis