基于离散随机分离的齿轮箱复合故障分析法

齿轮箱复合故障中,较弱的故障特征往往被较强的故障信号所淹没,传统方法较难实现对较弱故障特征的提取。为解决上述问题,提出一种基于离散随机分离的齿轮箱复合故障振动分析法。该方法首先使用快速谱峭度算法获取对齿轮箱振动信号的共振带参数,依据该共振带参数设计带通滤波器及结合Hilbert变换实现对振动信号包络提取;之后应用角域重采样将时域包络信号转换到角域以消除转速波动影响;再应用离散随机分离对角域包络信号进行分离,分别得到齿轮故障和轴承故障对应的角域包络信号;最后,分别对角域包络信号进行包络谱分析获得齿轮、轴承故障的特征频率信息。试验结果表明,该方法可实现齿轮箱齿轮及轴承复合故障特征的有效提取。

ANALYSIS SCHEME FOR MULTI-FAULTS VIBRATION OF GEARBOX BASED ON DISCRETE RANDOM SEPARATION

To multi-faults of a gearbox,the strong fault feature vibration of gearing always interfered with rolling element bearing weak fault vibration.The traditional methods are difficult to extract the weak bearing fault feature.In order to solve the problem,a vibration analysis scheme for multi-faults vibration of gearbox based on discrete random separation(DRS) is proposed.In the proposed method,the resonance parameters of the gearbox vibration is obtained based on the fast kurtogram algorithm at first,built a bandpass filter that included resonance parameters,and the envelope is extracted by Hilbert transform.Then,converted envelope to the angle domain based on the equi-angle increment resampling to remove speed fluctuation.Next,the SANC is performed to separate the envelope in the angle domain.As a result,the gear fault corresponding envelope component and the bearing fault related envelope component are obtained;Finally,the spectrum analysis is carry out on the two envelope components respectively for the fault diagnosis information.Test results show that this method can be used to extract the gear and bearing fault features effectively.