基于OSF的SET信号重构方法及故障诊断应用

同步提取变换(synchroextracting transform, 简称SET)通过提取短时傅里叶变换(short-time Fourier transform, 简称STFT)在瞬时频率位置的时频系数可获得较理想的时频谱，该方法提高了时频分辨率，减少了交叉项的影响，一定程度上抑制了噪声对STFT时频谱的干扰。针对在SET时频谱的基础上进行信号分量的重构与故障诊断拓展方面的应用，提出了一种基于顺序统计滤波器(order statistics filter, 简称OSF)的SET信号分量重构方法。首先，利用边际谱表征SET时频谱中信号的幅值在整个频率范围内随频率变化的情况；其次，采用顺序统计滤波器分割边际谱，将分割所得边界映射至SET时频谱后，利用SET逆变换重构信号分量；最后，利用峭度指标筛选包含丰富故障信息的分量并进行包络分析，提取故障特征。仿真信号及滚动轴承内圈故障信号的处理结果证明了该方法的有效性。

Reconstruction Method of Synchroextracting Transform Signal Based on OSF and Its Application in Fault DIagnosis

Synchroextracting transform (SET) can obtain the ideal time-frequency spectrum by extracting the time-frequency coefficient of the short-time Fourier transform (STFT) at the immediate frequency position. On the one hand, the method improves the time-frequency resolution, on the other hand, it reduces the influence of the cross terms, and suppresses the interference of the noise on the spectrum of the STFT to some extent. However, the reconstruction of signal components and the application of fault diagnosis based on the SET spectrum are still to be further studied.This paper proposes a SET signal component extraction and reconstruction method based on order statistics filter (OSF).Firstly, the marginal spectrum is used to characterize the amplitude of the signal in the spectrum when the SET changes with frequency in the whole frequency band, and then the margin spectrum is divided by the order statistics filter. Each of the signal components is reconstructed by the SET inverse transform after mapping the segmentation obtained boundary to the SET time spectrum. The shock-sensitive kurtosis index is used to screen the components of each component that may contain faults, and the effectiveness of the proposed method is demonstrated by the simulated signal and the inner ring fault signal of the rolling bearing.