【摘要】 与轴承、定轴齿轮箱相比,提取行星齿轮箱的故障特征更加困难,且传统方法对行星齿轮箱的诊断效果不好。针对行星齿轮箱故障振动信号的非线性、复杂性等特性,提出一种基于小波包样本熵和均方根值的故障特征提取新方法。该方法首先对原始信号进行连续等长度截取,获得样本信号,再利用小波包变换分解样本信号,计算分解后各频段的样本熵和均方根值,并进行归一化处理。将归一化参数作为加权平均的权重,计算加权平均的样本熵和均方根值。最后将两参数做商得到新参数。故障诊断及抗噪试验结果表明,新特征提取方法能增大行星齿轮箱不同故障特征的区分度且有较好的稳定性,同时新参数具有一定的抗噪性。更多还原

【Abstract】 Compared with bearing and fixed axle gearboxes, it is more difficult to extract the fault characteristics of the planetary gearboxes. And the traditional method is not good enough for the fault diagnosis of planetary gearboxes. In this paper, a new method of fault feature extraction based on wavelet packet entropy and RMS is proposed so as to find the nonlinear and complex characteristics from the fault vibration signals of planetary gearboxes. Firstly, the original signal is equally intercepted to obtain sample signals. Then, the wavelet packet transform is used to decompose the sample signals,and the sample entropy and RMS value of each frequency band are calculated and normalized. The normalized parameter is used as the weight of the weighted average to calculate the weighted average sample entropy and RMS value. Finally, the two parameters are used to get new parameters. The results of fault diagnosis and anti-noise test show that the new feature extraction method can enlarge the distinction of the characteristics of different faults of planetary gearboxes and has good stability. Meanwhile, the new parameters have some anti-noise ability.更多还原