基于EEMD和THT的齿轮故障诊断方法

Gear Fault Diagnosis Based on Ensemble Empirical Mode Decomposition and Teager-Huang Transform

提出了一种基于总体平均经验模态分解(ensemble empirical mode decomposition,简称EEMD)和Teager-Huang变换的齿轮箱故障诊断方法,该方法首先运用EEMD方法,将振动信号分解成不同特征时间尺度的单分量固有模态函数,然后用Teager能量算子计算各固有模态函数的瞬时频率和瞬时幅值,得到Teager-Huang变换时频谱。齿轮箱齿轮裂纹故障振动试验信号的研究结果表明,Teager-Huang变换时频谱优于Hilbert-Huang变换时频谱,能有效识别齿轮故障。

A new approach to fault diagnosis of gear crack based on Ensemble Empirical Mode Decomposition(EEMD) and Teager-Huang transform(THT) is presented.First,the original times series data is decomposed into intrinsic oscillation modes by using EEMD approach.Then the Teager Kaiser Energy Operator(TKEO) technique is applied to each intrinsic mode function(IMF).The TKEO can track the modulation energy and estimate the instantaneous amplitude and instantaneous frequency,and the time-frequency distribution can be obtained.Therefore,the characteristics of the gear faults can be recognized according to the time-frequency spectrum.The experimental results show that Teager-Huang transform based on EEMD can effectively diagnose the faults of the gear crack.