基于自适应共振解调技术的滚动轴承故障诊断
Fault Diagnosis of Rolling Bearing Based on Adaptive Resonance Demodulation Technique

针对现有共振解调技术中高频共振中心频率及滤波带宽确定方法不成熟的问题，提出了自适应共振解调技术。利用经验模态分解将故障信号分解成若干个固有模态函数，通过信息熵最小的固有模态函数分量确定高频共振频率，自适应选取带通滤波器的中心频率和带宽。利用Hilbert变换对滤波后的信号进行解调分析，得到包含故障特征信息的低频包络信号，提取故障特征频率，实现故障辨识。与现有共振解调方法相比，自适应共振解调方法在工程实际中应用性更强。
Aiming at the difficult problems of determining center frequency of high-frequency resonance and selecting bandwidth of the band-pass filter in the current resonance demodulation technique, an adaptive resonance demodulation technique was used to overcome the drawbacks. The key point of the method is to select adaptively center frequency and bandwidth of band-pass filter. Firstly, the fault signal is decomposed into several intrinsic mode functions (IMF) by empirical mode decomposition (EMD) technique; then, the information entropy of IMF component is calculated, the smallest component of information entropy to determine high-frequency resonance frequency is selected; finaly, the Hilbert transform is used to demodulate the envelope signals after band-pass filter, which obtain low-frequency signal of fault characteristic information. Compared with the existing resonance demodulation method, the adaptive resonance demodnlation method shows better for rolling bearing fault diagnosis in engineering practice