基于小波双谱的矿用齿轮箱故障诊断

Mine gearbox fault diagnosis based on wavelet and bispectrum

针对矿用齿轮箱振动信号的非平稳、非高斯等特点,提出了一种小波双谱分析的齿轮箱故障诊断方法。利用小波分解可将齿轮箱的振动信号分解到对应不同特征频率的频带,以提高频率分辨率和信噪比,然后有针对性地选择故障特征频率较明显的频带信号进行重构,并做双谱分析,以实现齿轮箱的有效故障诊断。实例表明,小波双谱分析是一种十分有效的齿轮箱故障诊断方法,它更能揭示故障齿轮箱振动信号的非平稳和非线性相位耦合特点。

Aiming at the non-stationary and non-gauss characteristics of vibration signal resulted from mine gearbox,a fault diagnosis method based on wavelet and bispectrum was proposed.In order to improve frequency resolution and signal-to-noise ratio（SNR）,the vibration signal of mine gearbox can be decomposed into some frequency bands,which have different feature frequency respectively.For achieving effective fault diagnosis of gearbox,frequency band signal with typical fault characteristic was selected for reconstruction,and then for analysis with bispectrum.The result of diagnosis example shows that wavelet and bispectrum analysis is an effective method for gearbox fault diagnosis,and it still demonstrates the unstable and non-linear coupling characteristics of gearbox vibration signal.