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包络分析已经被广泛地应用于轴承的故障诊断中。其核心思想是利用一带通滤波器提高轴承故障信号的信噪比,然后利用包络解调分析提取低频轴承故障特征。谱峭度能有效地自动寻找轴承共振频率带,并用来提升轴承故障信号的信噪比,但由于其带通滤波后的高频轴承故障信号受到振动传递通道的影响,轴承故障特征时域分辨率能力仍较低。在高信噪比条件下,盲均衡算法能有效地去除传递通道的影响,提升轴承脉冲力时域分辨能力。因此,文中提出了一种新的轴承故障诊断算法,利用谱峭度和盲均衡算法提取轴承时域故障脉冲力。结果表明,该方法能有效地提高轴承故障时域检测能力。
Envelope analysis has been widely used in bearing fault diagnosis. The core idea is to use a band-pass filter to improve the signal-noise ratio of the bearing fault signal, and then use the envelope demodulation analysis to extract the low-frequency bearing fault features. Spectral kurtosis can effectively find the bearing resonance frequency band automatically, and used to improve the signal-noise ratio of the bearing fault signal. However, due to the influence of the vibration transmission path of the high-frequency bearing fault signal with band-pass filter, Rate ability is still low. Under the condition of high signal-to-noise ratio, the blind equalization algorithm can effectively remove the influence of the transmission channel and improve the time-domain resolution of the bearing pulse force. Therefore, a new bearing fault diagnosis algorithm is proposed in this paper. The spectral kurtosis and blind equalization algorithm are used to extract the fault impulsive force in bearing time domain. The results show that this method can effectively improve the detection ability of bearing fault time domain.