基于小波包和LCD的滚动轴承故障诊断

Application of Bearing Fault Diagnosis Based on Wavelet Packet and LCD

针对含噪背景下提取滚动轴承的非平稳非线性信号特征的问题,提出了一种将LCD(局部特征尺度)与小波包相结合的故障诊断方法。对待测信号进行小波包降噪预处理,再利用LCD分解得到ISC分量(内禀尺度分量),进一步根据峭度-相关系数筛选真实ISC分量用以重构获得有效的故障特征信号。最后通过对重构故障信息进行能量算子包络解调,从而得到轴承故障的特征频率。将基于LCD和小波包的时频分析方法引入轴承故障诊断中,实验结果表明该方法能有效地提取机械故障振动信号的特征。

Aiming at the problem of non-stationary nonlinear signal characteristics of rolling bearing under the background of noise, a fault diagnosis method combining LCD ((Local Characteristic-scale Decomposition) with wavelet packet is proposed. First, the wavelet packet denoising pretreatment is treated with the measured signal, and the ISC component(Intrinsic Scale Component,ISC) is obtained by using LCD decomposition. Then the real ISC component is screened according to the cliff-correlation coefficient to reconstruct and obtain the effective fault characteristic signal. And last, the energy operator envelope demodulation of the reconstructed fault information is carried out to obtain the characteristic frequency of the bearing fault. The time-frequency analysis method based on LCD and wavelet packet is introduced into bearing fault diagnosis, and the experimental results show that the method can effectively extract the characteristics of mechanical fault vibration signal.