基于瞬时故障特征频率趋势线和故障特征阶比模板的变转速滚动轴承故障诊断

针对难以从滚动轴承的时频分布中提取瞬时转频分量的问题，本文利用由轴承包络时频谱中提取的瞬时故障特征频率替代传统瞬时转频实现重采样，进而基于故障特征因子与转频阶比边带构造故障特征阶比模板以实现变转速运行模式下滚动轴承故障诊断。其具体算法由以下四个部分组成：首先，联合应用谱峭度滤波算法与短时傅里叶变换得到能够突出瞬时故障特征频率的包络时频谱；其次，提出基于幅值重调的峰值搜索算法对瞬时故障特征趋势线进行提取；再次，以瞬时故障特征频率趋势线为基础对原信号进行故障相角域重采样并得到故障特征阶比谱；最后，根据被监测轴承的故障特征因子构造故障特征阶比模板对滚动轴承的运行状态与故障类别进行判断。仿真算例和应用实例将对该算法的有效性予以证明。

The instantaneous fault characteristic frequency and fault characteristic order template based fault diagnosis algorithm for rolling bearing under time-varying rotational speed

To solve the problem that there exist no clear and prominent components related to rolling bearing rotational frequency in the time-frequency representation, the instantaneous fault characteristic frequency from the envelope TFR is used as the substitute of the traditional rotational frequency to fulfill the resampling process and then a fault diagnosis algorithm for the rolling bearing based on the fault characteristic order template is proposed to accomplish the final bearing diagnosis. In specific, the proposed algorithm can be summarized as four parts: (1) The spectral kurtosis based filtering, together with the short time Fourier transform (STFT) can lead to the envelope TFR, (2) a revised peak searching algorithm is then used to extract the IFCF trend from the envelope TFR, (3) the resampling step is then carried on using the IFCF trend and the fault characteristic order (FCO) spectrum in the fault phase angle domain is obtained, (4) The fault characteristic order template based on the fault characteristic coefficient (FCC) is finally constructed to recognize the operating state of the rolling bearing under time-varying rotational speed and identifying its corresponding fault type. The effectiveness of the proposed method has been validated by both simulated and experimental bearing vibration signals.