基于BLCD和小波域双谱的齿轮故障诊断方法

本文对固有时间尺度分解(Intrinsic time-scale decomposition，简称ITD)方法进行了改进，提出了基于B样条的局部特征尺度分解方法(B spline-based Local characteristic-scale decomposition，简称BLCD)，在此基础上将BLCD与小波域双谱相结合应用于齿轮故障诊断。首先将BLCD方法和ITD方法进行对比分析，验证BLCD方法的优越性。然后采用BLCD方法将齿轮振动信号进行分解，得到若干个ISC分量(Intrinsic scale component，简称ISC)，再对ISC分量进行小波域双谱分析，通过双谱中峰值个数和耦合频率的成分来判断齿轮是否发生了故障。实验数据的分析结果表明，基于BLCD和小波域双谱的齿轮故障诊断方法能有效地应用于齿轮的故障诊断。

A Gear Fault Diagnosis Method Based on BLCD and Wavelet Domain Bispectrum

In this paper,the intrinsic scale component method is improved.A new method is provided,which is called B spline-based local characteristic-scale decomposition method (BLCD ).Then the BLCD method and wavelet domain bispectrum is used to diagnose the gear. Firstly, this article is analysed the BLCD and ITD with each other, which can be seen that the BLCD method has obvious advantages. Secondly, the gear vibration signals are decomposed adaptively into some intrinsic scale components by using the BLCD method. At last, the wavelet domain bispectrum method is used to analyse the ISC, the dual spectrum peak numbers and coupling frequency components is used to judge gear fault feature information, the experimental results show that, based on BLCD and wavelet domain bispectrum method can be effectively applied to gear fault diagnosis.