基于Teager峰值能量的低转速轴承故障特征提取方法

Fault feature extraction of low speed roller bearings based on Teager peak energy

峰值冲击是轴承故障信号中的重要特征之一,明显的峰值冲击有利于其故障诊断,而低转速工况下轴承故障由于振动能量小,峰值冲击微弱,导致故障特征容易被噪声淹没,通常无法通过包络分析等方法提取。为了增强微弱故障信号中的峰值冲击,提取低转速轴承故障特征,提出了基于Teager峰值能量的故障特征提取方法。采用移动窗口截取原信号,计算截取信号段的峰峰值,从而构造峰峰值特征波形,增强故障信号中的峰值冲击;利用Teager能量算子对峰峰值特征波形进行解调,抑制噪声干扰,提取瞬时冲击成分;根据提取的Teager能量频谱判断轴承的运行状态。实验结果表明,该方法有效提取了低转速轴承的冲击特征,实现了故障的诊断。

The peak impact is one of the most significant features in faulty signals of roller bearings and obvious peak impact is helpful to the fault diagnosis. However, when the roller bearings are operated at low speed, the fault features are easily submerged by the noise due to the small vibration energy and weak peak impact. Thus, the fault features cannot be extracted by the traditional methods, such as the envelope analysis. To enhance the peak impact in the weak faulty signals and extract the fault features successfully, a fault feature extraction method based on the Teager peak energy is developed. First, the raw signals are divided into several segments by a sliding window and the peak-to-peak value is utilized to represent each segment, through which the peak-to-peak symptom wave can be obtained, which can enhance the peak impact in the faulty vibration signals. Second, the Teager energy operator is applied to demodulate the symptom wave, which can eliminate the noise and extract the impact component. Finally, the status of the roller bearings can be determined by the spectrum of Teager energy. The experimental results show that the proposed approach can successfully extract the fault features of the low speed roller bearings and identify the performance of roller bearings accurately.