基于DT-CWT和奇异能量差分谱的滚动轴承故障诊断研究

Fault Diagnosis Research of Rolling Bearing Based on DT-CWT and Energy Difference Spectrum of Singular Value

滚动轴承故障信号具有非平稳、能量低等特征,为了能够准确、有效地检测出轴承故障,提出了将双树复小波和奇异值能量差分谱相结合的诊断方法。首先运用双树复小波对采集到的振动信号进行分解,再重构单支信号,由于噪声的干扰,从重构后分量的频谱中很难对故障做出正确的判断。然后对包含故障特征的分量求取奇异值能量差分谱,确定有效阶次进行信号重构降噪。最后对降噪信号求Hibert包络谱,便能准确获得故障特征频率。通过信号仿真和实验数据分析验证了该方法的有效性。

Rolling bearing fault signal is non-stationary and lower energy characteristics,in order to be able to accurately and effectively detect the bearing fault,which puts forward dual tree complex wavelet and energy difference spectrum of singular value diagnosis method of combining. First of all,the dual tree complex wavelet adopted to collect vibration signal is decomposed,and then reconstruct single signal. Due to the interference of noise,it is difficult to from the component of the spectrum reconstruction for failure to make the right judgment. Then,aimed at the containing fault feature component calculating for its energy difference spectrum of singular value it determines the order of the effective signal to eliminate the noise of signal reconstruction. Finally,the fault frequency can be obtained accurately by Hilbert envelope spectrum. Through the signal simulation and experimental data analysis it verifies the effectiveness of the proposed method.