摘要
提出了一种基于Teager-Huang变换的齿轮箱故障诊断方法,该方法综合利用了经验模态分解(empiricalmode decomposition,简称EMD)和Teager能量算子分析技术。由于EMD方法具有自适应的分析能力,首先利用EMD把时间序列信号分解成不同特征时间尺度的固有模态函数,然后用Teager能量算子计算各固有模态函数的瞬时幅值和瞬时频率,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,能有效地识别齿轮的裂纹故障。
A new approach to crack fault diagnosis of a gear based on the Teager-Huang transform is presented.This method integrates the empirical mode decomposition(EMD)with the Teager Kaiser energy operator(TKEO)technique.The EMD method is self-adaptive to non-stationary and non-linear signal analyses.The method developed in this paper decomposes original times series data into a series of zero mean amplitude modulation-frequency modulation(AM-FM)intrinsic mode functions(IMFs)by using EMD.TKEO can track the instantaneous amplitude and frequency of the AM-FM component at any moment.Experimental examples were conducted to evaluate the effectiveness of the proposed approach.The results show that the performance of the Teager-Huang transform is better than that of the Hilbert-Huang transform for gear fault monitoring and can effectively diagnose the gear crack faults.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2010年第1期1-5,共5页
Journal of Vibration,Measurement & Diagnosis
基金
国家自然科学基金资助项目(编号:50975185
50775219)
