基于信号共振稀疏分解的阶比分析及其在齿轮故障诊断中的应用

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An order domain analysis method based on resonance-based sparse signal decomposition was proposed to extract the fault characteristic frequency from the vibration signal of a fault gearbox with rotating speed fluctuation.The resonance-based sparse signal decomposition method decomposes signal into two parts： the ‘high-resonance’component and ‘low-resonance ’ component.The ‘low-resonance ’ component is an impact signal consisting of non-oscillatory transients with unspecified wave shape and time duration.The chirplet path pursuit algorithm was used to obtain the rotating speed signal of the gearbox.According to the rotating speed signal,the time domain impact signal of the gearbox was resampled at constant angle increments.Carrying out the spectral analysis on the resampled impact signal,the order domain analysis was accomplished and the final diagnosed results could be obtained accordingly.The proposed approach is of good anti-noise ability,and is suitable for analyzing the actual vibration signal of a gearbox with rotating speed fluctuation.An practical application example proves the validity and superiority of the proposed method.为从非平稳转速齿轮箱故障振动信号中有效提取包含故障信息的特征频率,提出一种基于信号共振稀疏分解的阶比分析方法。故障齿轮振动信号中主要包括瞬态冲击成分和周期谐波,该方法先采用信号共振稀疏分解方法将信号分解为高共振分量和低共振分量,提取出故障冲击信号,然后采用线调频小波路径追踪算法对原信号提取转频信息,利用转频对提取的故障冲击信号进行阶比分析,从而得到故障诊断结果。非平稳转速齿轮故障诊断实例表明,该方法可有效提取冲击信号,诊断转速波动齿轮的故障。