【摘要】 早期的轴承故障振动成分中包含大量的噪声成分，严重干扰了循环谱中的特征辨识。为解决这一问题，提出谱峭度增强循环谱的轴承早期微弱故障诊断方法。通过谱峭度滤波选出故障特征频带，抑制强噪声干扰；再经过谱峭度协助后在循环谱图中能够凸显故障特征，从而实现更早期轴承故障诊断。通过仿真、实验和工程数据分析证明了所提出方法的优越性和有效性。更多还原

【Abstract】 To address the issue of massive noise components in the early stage of bearing vibration fault which seriously interfers the feature identification of cyclic power spectrum, this paper proposes a kurtosis-assisted cyclic power spectrum method for early weak fault diagnosis of bearings. The fault characteristic frequency band is selected through kurtosis filtering to suppress strong noise interference. With the kurtosis assistance, the fault features is highlighted in the cyclic spectrum density plot, enabling earlier bearing fault diagnosis. The simulation, experiment and engineering data analysis verify the superiority and effectiveness of the proposed method.更多还原